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Journal Articles

Journal:
SPE Drilling & Completion

Publisher: Society of Petroleum Engineers (SPE)

*SPE Drill & Compl*20 (03): 179–186.

Paper Number: SPE-84839-PA

Published: 01 September 2005

... cement and bond evaluation The

**Value**of Cement Innovation: Reduced Cycle**Time**Saves**Money**Roger Myers, SPE, David J. Mack,* SPE, Daniel Kendrick, SPE, George Woo, SPE, BJ Services Co.; David Matz, SPE, Dynatec Corp.; and Derek Hina SPE, Equitable Production Co. Summary Lightweight, low-compressive...
Abstract

Summary Lightweight, low-compressive-strength cement slurries save Appalachian basin operators thousands of U.S. dollars per well when compared with two-stage cement jobs using a packer-collar tool. The average amount of annular fill-up that is required in the typical southern West Virginia Devonian shale well is3,000 ft. Because the shale is naturally fractured and has a low fracture gradient of 0.3-0.4 psi/ft, many operators opt to cement the air-drilled, unconventional gas wells with a 12-ppg lightweight silicate cement. Over the past 5 years, more than 800 wells have been cemented with water-extended cement slurry, pumped at 12 ppg. Interestingly, the cement's compressive strength in 72 hours measures only 500–700 psi, not nearly enough to be "seen" with the cement-bond logging tools most commonly employed. In fact, at least one operator waits a full 7 days before running a variable-density log because that is about the time needed for the cement to develop enough compressive strength and acoustical impedance to be seen. While solving one problem related to cutting authorized-for-expenditures well costs, the lightweight cement caused another problem: lost production days because of waiting on cement (WOC). Using knowledge of available Portland cements and a proprietary compressive-strength enhancing agent, a new cement blend was developed that could get higher strengths and better acoustical impedance. This paper will document how one large northeast operator successfully solved the problem of cycle-time reduction while maintaining the cement density at 12 ppg. Key aspects related to the solution, including laboratory testing of the cement and cement additives and examples of post-solution cement-bond logs, will be shown. Economics related to lost days of production over a 100-well drilling program will also be discussed.

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, April 2–3, 2001

Paper Number: SPE-68595-MS

... virtually untouched by the higher discount rate. First principles tell us that discount rates measure

**time****value**of**money**, not risks. Some analysts do FMV determinations failing to recognize the effects of competition. The identification and ramifications of the Winner's Curse enlighten us that a winning...
Abstract

Abstract A lesson from college physics: If you get lost, start over at F=ma (force=mass×acceleration). We can use that same strategy for property evaluation where similar first principles apply. In a survey sponsored by the SPEE, respondents say they use discount rates of 20% or more. First principles tell us that the discount rate and the reinvestment rate should be the same. Using over a century of data, Siegel's STOCKS FOR THE LONG RUN shows that average returns for companies have been 5% after tax and after inflation. Not 20%. Either Siegel errs or respondents have no clue. Consultants often raise discount rates to account for risks. Say the uncertainty for a project lies mostly in the cost to get production started. Raising the discount rate to account for cost uncertainty affects every yearly cash flow except the one with which we're uncomfortable. Initial investment remains virtually untouched by the higher discount rate. First principles tell us that discount rates measure time value of money, not risks. Some analysts do FMV determinations failing to recognize the effects of competition. The identification and ramifications of the Winner's Curse enlighten us that a winning offer is not a reliable value estimate. First principles teach us that an auction winner because of his high side bias cannot claim to be "equally knowledgeable," a basic phrase to the FMV definition. Misuse of the Capital Asset Pricing Model has mislead many executives into setting unreasonably high target returns. Academics signed on to a simple formula that they claimed captured the subjective investment decision making practices of a hundred million individuals. First principles inform us that no one has found such a formula because human behavior is unpredictable. The paper describes these and a dozen other similar evaluation problems. Introduction Sometimes when confusion reigns, we should return to our roots. Go back where it all started. Examine first principles. I can think of few places where such a strategy would be more appropriate than in the valuation of oil and gas properties . Many of those who purport to dispense expert advice have no personal stake in the outcome though they may find some reward for supporting a particular view. No wonder lots of bad counsel gets spread around like so much fertilizer. One of the more egregious errors we find in oil and gas valuations today is 1) the confounding of risk, the potential for damage or loss, and 2) the discount rate which measures the time value of money. The first requires application of objective probability analysis and subjective tolerance for uncertainty. The 2nd leans mostly on objective criteria found in the public financial records of companies doing business in oil and gas. We'll examine this problem as well as others that introduce errors into oil and gas evaluation. You should find a fully self-contained paper here. These pages hold all the evidence for all of the arguments. With this simple presentation of facts I would not expect any reader to bog down, require help from others, or retreat to the familiar, "well that's not the way I was taught." In this paper I'm going to try to take care with the definitions. Risk means the potential or chance for loss.1 Uncertainty means a lack of knowledge about what the future holds. From analyzing uncertainty we uncover the effects and size of risk. Risk ? uncertainty. Opportunity Consider the following investment. You give me $40 dollars now. A disinterested 3rd party will activate a well balanced spinner with 3 equal colored segments. If the spinner's arrow head lands in the blue, you (or your heirs) win $100. If it lands in the red, you (or heirs) win $80. Otherwise you get nothing. The heirs come into play because the payoff occurs 6 years from now. Prudential guarantees payment via an arrangement I make with them should I not survive to fulfill my obligation to you. Moreover I'll agree to play this game with you every hour of the day so you don't have to face the so-called single opportunity problem. We identify three distinct considerations. One, the uncertainty of whether or not the spinner lands in your favor and two, the time value of money since you must invest today for a possible payoff in 6 years. Risk? Yes, you may lose money. Expected Value and Variance When you have more than one possible outcome, you must spell out each or at least enough of them to get a good handle on the variability to expect. In this simple example you get either $0, $100, or $80. How does one describe such a game? You could say that it has the potential for a $100 payoff and make your decision on that basis. You could note that you have a 2/3 chance of winning and only a 1/3 chance of losing and make your decision accordingly. We know better ways.

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the Oil and Gas Economics, Finance and Management Conference, June 8–9, 1994

Paper Number: SPE-28192-MS

... of a discount rate to adjust for the

**time****value**of**money**, and (4) some techniques to reflect the market price of risk. The most common approach to DCF analysis uses the Capital Asset Pricing Model (CAPM) to measure the market price of risk in the form of a risk premium to be added to the**time****value**of**money**...
Abstract

Abstract The management of any petroleum company is charged with allocating resources among potential investment opportunities. Determination of the appropriate discount rate is a critical element in the analysis of these opportunities using discounted cash flow techniques. The appropriate discount rate is affected by a number of factors, some a matter of macroeconomic conditions (e.g., inflation and interest rates), some a matter of company policy (capital structure), and some specific to the particular project. This paper discusses (1) the general methodology for estimating company-average discount rates, reflecting both macroeconomic factors and company policy choices, and (2) the circumstances under which the company-average rate is likely to be significantly inappropriate and the adjustments that can be made under those circumstances. Background The resource allocation problem can be expressed as the need to measure the value today of a stream of uncertain cash flows in the future. The traditional discounted cash flow (DCF) approach to this problem requires (1) estimation of future cash flows, (2) estimation of the uncertainty surrounding each of those cash flows, (3) estimation of a discount rate to adjust for the time value of money, and (4) some techniques to reflect the market price of risk. The most common approach to DCF analysis uses the Capital Asset Pricing Model (CAPM) to measure the market price of risk in the form of a risk premium to be added to the time value of money. Thus, in practice, the discount rate in the DCF analysis combines steps 3 and 4 above, and reflects both the time value of money and the market price of risk. Academic research has called into question the empirical accuracy of CAPM. However, the intuition underlying the model is quite powerful, and the model itself is simple enough that it can be implemented as a practical tool to aid corporate decision-making-provided that is correctly understood. P. 53^

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the SPE Annual Technical Conference and Exhibition, October 4–7, 1992

Paper Number: SPE-24650-MS

... then in vogue failed to account properly for the

**time****value**of**money**. This was also the era of the desk calculator and slide rule. Simplification of the reservoir calculations was a desirable part of what was a laborious manual calculation process. What we did quite simply was to borrow**time****value**of**money**...
Abstract

SPE Member Abstract In the restructuring process of the petroleum industry let us not forget the basic decision methods which contributed to its current adversity. The emphasis to date has been on the elimination and/or reorganization of personnel. Cutting costs may be expedient on a short-term basis but as a long term strategy, it is merely a step toward going out of business. As in any intelligent decision process, any examination of our evaluation methods requires understanding their origins, how they changed from then to now, and their current applicability. This paper is a summary of the authors view of these matters. Hopefully, it will catalyze some long overdue scrutiny of the conventional methods to better understand their current significance, which in turn will result in a new evaluation paradigm. Introduction The evaluation methods used today are essentially the same as those proposed in my 1959 book. This was a compendium of the work of a relatively small group of professionals of which Jan Arps, Harold Vance, Folkert Brons, and the author were particularly visible. A good summary of the contributors and their key papers is found in References 1–4. No new technology was involved. The system was devised to meet then current needs based an a logical, practical application of existing technology from a variety of sources. So… nothing in this evaluation process is unique to the oil and gas industry except some of the nomenclature and nature of the "warehouse" being analyzed. Table 1 summarizes the scenario for operations in the middle 1950's. Things were relatively simple. One primary motivation to modify the then traditional practices was the larger investments involved in the new offshore industry and the subsequent increases in payout time. The traditional methods then in vogue failed to account properly for the time value of money. This was also the era of the desk calculator and slide rule. Simplification of the reservoir calculations was a desirable part of what was a laborious manual calculation process. What we did quite simply was to borrow time value of money concepts (which had been around for a long time), and combine them with some correlations from hopefully analogous systems along with convenient volumetric methods and production rate curves. We called the latter "decline curves" since the rate of most primary production went down with time. Consider these things and compare Table 1 with the present day scenario. P. 189^

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the SPE Hydrocarbon Economics and Evaluation Symposium, May 19–20, 2014

Paper Number: SPE-169875-MS

... receive in projects governed by fiscal arrangements such as Production Sharing Contracts (" PSCs "); b) ignores abandonment costs and income tax liabilities, even though these are real and often material cash outflows; and c) appears to ignore the

**time****value**of**money**. These shortcomings can cause the PRMS...
Abstract

This paper offers a critique of, and suggests an alternative to, commonly used methods – including the method stipulated in the 2011 Guidelines for Application of the Petroleum Resources Management System (hereafter, " PRMS Guidelines "), promulgated by the SPE and others – for calculating the economic limit test (" ELT ") for upstream petroleum projects. The ELT determines the assumed project abandonment date. In particular, the authors fault the PRMS Guidelines -prescribed ELT method because it a) uses a measure of revenue which is often much higher than what Investors actually receive in projects governed by fiscal arrangements such as Production Sharing Contracts (" PSCs "); b) ignores abandonment costs and income tax liabilities, even though these are real and often material cash outflows; and c) appears to ignore the time value of money. These shortcomings can cause the PRMS ELT to assume abandonment dates which result in Net Present Values (" NPVs ") of discounted future cash flows which are lower than an Investor could achieve by using a different abandonment date. In such cases, the PRMS approach is tantamount to Investor value destruction. This paper presents a simple, transparent and mathematically sound alternative ELT calculation method, which considers all Investor NPV-relevant items, including abandonment costs, income taxes, the time value of money, and, in the case of PSCs, actual Contractor cash revenue, to determine which abandonment date maximizes Investor NPV. The method avoids the circularity which can arise when attempting to consider abandonment costs while calculating a future uncertain abandonment date. The paper compares the results of using the authors' method and the PRMS method in example valuations. These examples show that the authors' method can result in different economic limits/abandonment dates – and thus higher NPVs – than the PRMS method. The authors' underlying Microsoft Excel model accompanies this paper. The findings are relevant to value-focused investors -- especially those in projects which are governed by PSCs, and/or involve large abandonment liabilities pending in the short-term or long-term -- and to parties who issue or otherwise use PRMS standard valuations.

Journal Articles

Journal:
Journal of Petroleum Technology

Publisher: Society of Petroleum Engineers (SPE)

*J Pet Technol*51 (10): 44–49.

Paper Number: SPE-57894-JPT

Published: 01 October 1999

... they incorporate the

**time****value**of**money**; and whether they allow for managerial flexibility. We show that, despite their obvious differences, they are in fact different facets of a general project-evaluation framework that has the static base-case scenario as its simplest form. Compromises have to be made when...
Abstract

This paper (SPE 57894) was revised for publication from paper 52949, originally presented at the 1999 SPE Hydrocarbon Economics and Evaluation Symposium held in Dallas, 20–23 March. Original manuscript received 3 January 1999. This paper has not been peer reviewed. Summary Option pricing, decision trees, and Monte Carlo simulations are three methods used to evaluate projects. In this paper, we compare their similarities and differences from three points of view—how they handle uncertainty in the values of key parameters, such as reserves, oil price, and costs; how they incorporate the time value of money; and whether they allow for managerial flexibility. We show that, despite their obvious differences, they are in fact different facets of a general project-evaluation framework that has the static base-case scenario as its simplest form. Compromises have to be made when modeling the complexity of the real world. These three approaches can be obtained from the general framework by focusing on certainty aspects. Introduction Option pricing, decision trees, and Monte Carlo simulations are three methods for evaluating oil projects that seem at first radically different. Option pricing comes from the world of finance. In its most common form, it incorporates the Black and Scholes 1 model for spot prices and expresses the value of the project as a stochastic differential equation. Decision trees, which come from operations research and games theory, neglect the time variations in prices but concentrate on estimating the probabilities of possible values of the project, sometimes with Bayes theorem and pre- and post-probabilities (see Ref. 2). In their simplest form, Monte Carlo simulations merely require the user to specify the marginal distributions of all the parameters appearing in the equation for the net present value (NPV) of the project. All three approaches seek to determine the expected value (or maximum expected value) of the project and possibly the histogram of project values; however, they make different assumptions about the underlying distributions, the variation with time of input variables, and the correlations between these variables. Another important difference is the way they handle the time value of money. Decision trees and Monte Carlo simulations use the traditional discount rate; option pricing makes use of the financial concept of risk-neutral probabilities. One of the difficulties in estimating the value of a project is that it usually is a nonlinear function of the input variables (for example, tax is treated differently in years with a profit than in years with a loss). Starting out from the NPV calculated on the base case, this paper shows how Monte Carlo simulations and decision trees build uncertainty and managerial flexibility into the evaluation method. Option pricing starts out by defining the options available to management and then models the uncertainty in key parameters. The three approaches are, in fact, different facets of a general framework. They can be obtained from this framework by focusing on certain aspects and simplifying or ignoring others. First Step-NPV for the base case The first step in evaluating any project is to set up a base-case scenario and to calculate its NPV with the parameter values that have been agreed upon. This assumes that the values of the input parameters are known: original oil in place, decline rate, oil prices for each year, costs for each year, discount rate, and tax structure, among others. It further assumes that the scenario and the project life are fixed and that management will not intervene because of changes in the oil price, new technological developments, and other such factors. In the real world, the values of the variables are uncertain and management does react to changing situations, so it is vital to incorporate these two factors into the evaluation procedure. Ideally, distributions of all the variables should be modeled together with the correlations over time and the complex links between variables should be modeled for a wide variety of management scenarios. However, as Smith and McCardle 3 demonstrated, this rapidly becomes very unwieldy and the sheer complexity of the situation forces compromise. Monte Carlo simulations, decision trees, and option pricing address this problem in different ways; each focuses on certain aspects and simplifies or ignores others. We show how these methods build up from the NPV equation in the base case incorporating uncertainty in the input variables for all three methods and incorporating managerial flexibility for decision trees and option pricing.

Journal Articles

Journal:
Journal of Petroleum Technology

Publisher: Society of Petroleum Engineers (SPE)

*J Pet Technol*52 (02): 56–61.

Paper Number: SPE-60223-JPT

Published: 01 February 2000

... of valuation consists of an annual forecast of oil and gas production volumes

**times**a prediction of prices less an estimate of operating costs. After other, but minor, adjustments, this future cash flow is discounted for both**time****value**of**money**and the perceived probability of achieving exactly the predicted...
Abstract

This paper (SPE 60223) was revised for publication from paper 52957, originally presented at the 1999 SPE Hydrocarbon Economics and Evaluation Symposium held in Dallas, 20–23 March. Original manuscript received 1 February 1999. This paper has not been peer reviewed. Summary Valuation of non-U.S. concessions, prospects, and producing fields varies greatly from country to country because of differences in fiscal and political regimes and therefore must include quantified adjustments for these differences in the light of comparative modes of sale of other non-U.S. properties. The market for acquisitions and divestitures works by also applying such adjustments to the values derived for U.S. analogs with comparable geological, engineering, and economic risks. This paper discusses the primary types of fiscal regimes found around the world, namely, licenses with royalties and taxes, association agreements, and production-sharing contracts (PSC's). We show that discounted-cash-flow (DCF) models are readily applicable to proved reserves and present a review of a recent market transaction to demonstrate these effects. Political risk in the non-U.S. market is shown to be additive. Introduction For most of the 20th Century, non-U.S. oil business was the exclusive domain of industry majors. Over the last few decades, however, numerous small companies and independents have become increasingly global, which, in turn, increases the need to understand the approaches to valuing their non-U.S. properties. Takings or expropriations are experienced where values may need to be estimated by courts or tribunals. Other instances requiring a valuation include potentially taxable transactions, such as transferring an oil or gas property across country boundaries. Sales transactions frequently take place between apparently willing and knowledgeable buyers and sellers, so the concept of fair market value should apply. This all sounds familiar to the U.S. oilman, banker, or tax agent. However, can the same approaches to estimates of fair market value be used globally? Are there differences or pitfalls that would be important to consider when appraising non-U.S. properties? This paper shows that a resounding "yes" is the answer to both questions. It also highlights some of our own experiences in the non-U.S. appraisal arena. U.S. Approaches Numerous presentations have been made on the merits of conventional approaches, such as the DCF methods and comparable sales with various unit values. In addition, cost methods have seen use, particularly in the downstream sector. This paper examines the ease or difficulty with which these familiar methods can be applied worldwide. A brief review of the most common U.S. method, the DCF approach is presented first, followed by an alternative interpretation of the discount rate applied by the market. DCF Approach. The DCF method is best applied to producing properties or to properties where the outlook for an income stream in the near future is likely and not speculative. Simplistically, the multistep approach of valuation consists of an annual forecast of oil and gas production volumes times a prediction of prices less an estimate of operating costs. After other, but minor, adjustments, this future cash flow is discounted for both time value of money and the perceived probability of achieving exactly the predicted cash flow. Miller and Vasquez 1 present arguments for their observed 6 to 8% excess of the average market discount rate over the average cost of capital. The excess is sometimes considered equivalent to growth motive, offsetting the "risk" of the oil business. It reflects the desire on the part of owners or management to make a rate of return better than the company's weighted average cost of capital (WACC). Can this 6 to 8% excess be dissected further, and can it be quantified? Most importantly, can such an understanding improve the selection of discount rates to be applied in the valuation of non-U.S. properties? Key Variables. We examine the oil operating company's perception of the probability that it will actually receive the predicted cash flow when purchasing a producing property. If the company were 100% sure of the cash flow as predicted by the reserve engineer, it might pay close to its cost of capital. Conversely, if an operating company were uncertain, it would pay less and target a higher rate of return. Prediction of the DCF rate of return is based on four major parameters: production quantities, oil prices, operating costs, and discount rate. Production quantities may vary from the petroleum engineer's predictions, oil prices will fluctuate, and operating costs may likewise turn out differently than forecast. In addition, the discount rate generally used to reflect time value of money—namely, the weighted average cost of capital (WACC) for the E&P industry sector—varies with the country's economy. U.S. appraisal experience and literature provide a framework for estimates of these four parameters. Quantity, Price, and Operating Cost. The first three parameters have been used for prediction for almost 5 decades and applied in DCF forecasts for valuation of oil and gas properties.

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the Middle East Oil Show, June 9–12, 2003

Paper Number: SPE-81548-MS

... actual and financial impacts will give a clearer picture as to the outcome a project will achieve. The calculations are not dependent upon predicting future oil prices or assigning a

**time****value**to**money**. Conventional economic measurements (net present**value**(NPV), internal rate of return (IRR...
Abstract

Abstract Economics performed by projected cost per unit analysis will give better insight into the merits of an oil production project than conventional measurements. This alternative economic metric can easily be used to determine if the project meets the objectives of a particular oil company. The proposed method will give pertinent values to see if return on investment, return on capital employed, operating expense, and cash flow goals will be met. As an additional benefit, cost per unit analysis also incorporates all the accounting pseudo charges. The inclusion of all actual and financial impacts will give a clearer picture as to the outcome a project will achieve. The calculations are not dependent upon predicting future oil prices or assigning a time value to money. Conventional economic measurements (net present value (NPV), internal rate of return (IRR), profitability indexes) can be misleading as to the actual benefit the project has for an oil company. They require that you predict oil prices and, in the case of NPV, assign a time value to money. These typical economic measures were designed to compare one project against another. High IRRs for capital investments can be due to initially high oil production and/or high tax regimes that allow for accelerated depreciation. A good NPV is sometimes achieved just by the large size of a project. Examples will be shown how projects with excellent NPVs and IRRs turned into disastrous economic failures despite performing close to prediction. Using the alternative method described in this paper would assist in avoiding costly mistakes and will help achieve the financial goals a company aspires. Introduction Economic metrics have been used for decades to evaluate the merits of a particular project and to compare a range of projects to each other. Certain metrics have gained wide acceptance among all industries. These generally accepted measures (specifically NPV and IRR) have made it easy to present potential projects to groups of various backgrounds and from different organizations. Most people are comfortable with the standard metrics whether or not they truly understand them. There is not an apparent need to explain the calculations because whether a person's educational background is finance, engineering, or geology, he or she knows the terminology and has some background in the subject. It is curious that if the results from the most complicated decision analysis models are presented in the form of NPVs and IRRs, most individuals will give creditability to the outcomes. Presented in any alternative format, economic results will be given extreme scrutiny. The bottom line is that people are always more at ease with things they are familiar with. It is for the aforementioned reasons that when proposing an alternative economic analysis method, one must be cautious. Any new method must not be complicated or have any vagueness. More importantly a new economic measurement must be in some way clearly superior to those that already exist. Without meeting these two criteria, any new method will be dismissed out of hand. Cost per unit economics meets these criteria. The basics of cost per unit economics are straightforward. The calculations are not at all complicated. The analysis of the results will be only as involved, as the analyzer wants to make them. The results of the analysis will provide clear indication whether or not a project will help achieve the objectives of a company. Method of Calculation Quite simply, cost per unit economics (CPUE) has as its basis the unit cost of producing a barrel of oil or a MCF of gas. The elements necessary to do the analysis are the development costs, expected marketable hydrocarbons that the well or project will produce, the relevant actual operating expenses, and any accounting expenses. Knowledge of these values alone is enough to do the basic calculations. The analysis, not the calculations, thus becomes the more important criteria. As will be seen in the "Analysis of Results" and "Sample Analysis" sections, the analysis does not have to be complicated either.

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the SPE Annual Technical Conference and Exhibition, October 8–11, 1989

Paper Number: SPE-19710-MS

... as the cost of its components.

**Time****Value**of**Money**When combining both capital and power costs, the**time****value**of**money**must be considered. Figure 1 is a**time**line showing when each cost is incurred over the expected life of an ESP system. The capital cost (initial investment) occurs at**time**equal to zero...
Abstract

Abstract Electricity is a major cost associated with electric submersible pumps (ESPs). To help reduce ESP costs, Chevron Oil Field Research Company has developed a method of ESP design optimization which considers both capital cost and power cost. Application of the design method through an in-house computer program allows field personnel to easily compare systems of different vendors and select the one with the lowest total cost. Introduction ESPs account for a significant portion of Chevron's domestic total fluid production. Operation of these systems contributes a major portion of our electricity bills. Optimizing ESP designs to produce the well at the least possible electricity produce the well at the least possible electricity expense would help minimize these operating costs. This paper presents a method of ESP design optimization. The optimal ESP system is defined here as the one that will yield the desired production at the lowest combination of capital and power costs. Many existing ESP design methods generate systems that will produce the well but not necessarily at the least possible total cost (capital + power). ESP DESIGN OPTIMIZATION METHOD The ESP design optimization method follows the same logic as that of Vandevier in his ESP cable sizing routine. Vandevier showed that both capital cost and power cost should be considered when selecting the optimum ESP cable. We took this philosophy and applied it to the entire ESP system considering its total power consumption as well as the cost of its components. Time Value of Money When combining both capital and power costs, the time value of money must be considered. Figure 1 is a time line showing when each cost is incurred over the expected life of an ESP system. The capital cost (initial investment) occurs at time equal to zero; whereas, the power cost is expended at equal time increments over the system life. These two costs must be put on the same basis to make an accurate comparison. This may be accomplished two ways. one way is to use a present value interest factor of an annuity (FVIFA) to calculate the present value of all the power costs. This number can then be added to the capital cost to determine the total present value cost of a system. present value cost of a system. Total PV Cost ($) = Capital Cost + (PVIFA i,n* Power Cost) (1) 1 - (1 + i)-n PVIFA i,n = (1a) PVIFA i,n = (1a) i where: i = monthly interest rate n = system life, months Alternatively, a capital recovery factor (CRF) can be used to spread the capital cost over the life of the system. This number can then be added to the power cost to determine the total interval cost of power cost to determine the total interval cost of a system. P. 101

Journal Articles

Journal:
SPE Computer Applications

Publisher: Society of Petroleum Engineers (SPE)

*SPE Comp App*6 (03): 19–23.

Paper Number: SPE-26243-PA

Published: 01 May 1994

... payout indicates the liquidity of a project, it does not incorporate the

**time****value**of**money**or what happens after payout. Performing economic evaluations on the basis of payout of most likely expenditures and revenues can lead to optimistic expectations for low-risk workovers where costs exceed...
Abstract

Summary Implementing Monte Carlo methods on a PC can significantly improve risk assessment in the evaluation of workover opportunities. Monte Carlo simulation is a probabilistic method that allows the evaluator to consider an entire range of potential outcomes. This paper presents a method for implementing Monte Carlo methods in a PC environment to evaluate workover opportunities. Introduction Most oil and gas industry investments involve considerable risk and a wide range of potential outcomes for a particular project. However, many economic evaluations are based on most likely results without sufficient consideration of other possible outcomes. This approach is particularly true in evaluation of workovers where a simple payout figure is often used with a broad judgment of potential risks to determine the desirability of a particular workover operation. While payout indicates the liquidity of a project, it does not incorporate the time value of money or what happens after payout. Performing economic evaluations on the basis of payout of most likely expenditures and revenues can lead to optimistic expectations for low-risk workovers where costs exceed authority-for-expenditure (AFE) estimates or production rates are less than anticipated after the workover. On the other hand, this approach can also lead to pessimistic evaluations of high-risk workovers. Rike noted this dilemma and the need for improved evaluations of workover opportunities. He proposed use of a risk-adjusted payout and incorporation of time-value-of-money concepts and production life and investment requirements to improve evaluation of workover opportunities. Rike presented a method and equations to develop tables that would allow determination of the discounted profit/investment ratio (DPI) and rate of return (ROR) on the basis of the risk-adjusted payout to improve evaluation of workover operations. While Rike's approach is an improvement, the evaluation process still uses most likely estimates of workover costs and resulting revenue streams. It does not account for possible variations from the expected in oil and gas prices, workover costs, or production rates. The approach also anticipates that the risk factor used in the analysis will capture the mechanical risks of the operation and the reservoir risks of the uncertainty of geologic and engineering data used in the evaluation. While risk-adjusted methods have been proposed by others to evaluate petroleum-related projects, it is often difficult to quantify risk factors for various workover operations. Garb classified uncertainties into technical, economic, and political categories. Technical uncertainty deals with whether the estimates of reserves and production rates developed by engineers and geologists are accurate. Economic uncertainty relates to fluctuations in oil and gas prices, market conditions, workover costs, and inflation rates. Political uncertainty includes state, local, and national taxes; environmental regulations; global concerns; and how they can change. The total risk factor for a project is a product of technical, economic, and political uncertainties. Unfortunately, single risk factors can be quite subjective and biased by the evaluator's experience. Capen concluded from experimental data that people tend to overestimate the precision of their knowledge and consequently understate uncertainty, which can lead to optimistic results. Garb also made this point.

Journal Articles

Journal:
Journal of Petroleum Technology

Publisher: Society of Petroleum Engineers (SPE)

*J Pet Technol*67 (11): 71–73.

Paper Number: SPE-1115-0071-JPT

Published: 01 November 2015

... to measure financial performance or to make capital budgeting decisions. In addition to NPV, the metrics may include internal rate of return (IRR), real options analysis, or payback period. Among these, payback fails to account for the

**time****value**of**money**, IRR does not return a unique solution in cases where...
Abstract

Management Oil companies exist to make money. Many companies too often focus solely on maximizing current production when they should really be focusing on maximizing profitability. A holistic, total asset modeling process is needed to reorient the focus of digital oilfield systems to make the net present value (NPV) of every project the centerpiece of all decisions. Digital oil field providers have spent the past decade enabling a growing variety of specific workflows to automate isolated engineering tasks. These efforts have significantly reduced nonproductive time and costs. Nevertheless, transformational productivity increases will be required for operators to thrive in a prolonged, low oil price environment. For this reason, digital oil fields must become less about workflow orchestration and more about financial optimization. A variety of metrics are used in the industry to measure financial performance or to make capital budgeting decisions. In addition to NPV, the metrics may include internal rate of return (IRR), real options analysis, or payback period. Among these, payback fails to account for the time value of money, IRR does not return a unique solution in cases where positive and negative cash flows alternate over time, and real options analysis can be shown to be equivalent to the NPV method if risk is properly accounted for.* Less formalistic measurements may also come into play, particularly where projects involve national oil companies for whom politics, short-term cash flow pressures, and regulatory frameworks can exert large influences over the selection of a project. Without a significant loss of generality, we claim that if a business activity is not expected to increase NPV, then it should not be undertaken. Under this assumption, well-intentioned, but NPV-reducing, programs of activity that are proposed to improve a technical metric should be reconsidered. For example, reservoir engineers will always try to improve their recovery factors, but economic limits will dictate the scenarios in which oil should be left in the reservoir. In a company in which groups or teams are accustomed to operating in silos, the financial effect of decisions can be opaque, particularly at the level of decision making required to manage globally dispersed, cross- functional teams. To improve transparency, it is insufficient for only managers to have visibility into the financial effect of technical decisions. Technical personnel also need to know that their work is improving the bottom line. As they gain greater financial awareness, employees will begin making more improvements to their technical projects in ways that optimize profitability.

Journal Articles

Journal:
Journal of Petroleum Technology

Publisher: Society of Petroleum Engineers (SPE)

*J Pet Technol*39 (03): 263–271.

Paper Number: SPE-16449-PA

Published: 01 March 1987

... techniques in use today recognizes the

**time****value**of**money**, which isapplied by discounting future cash flows to present**value**at some particulardate. This gives meaning to the phrase "**time**is**money**." Purpose of Economic Analyses The purpose of an economic analysis is to determine the effect...
Abstract

Distinguished Author Series articles are general, descriptiverepresentations that summarize the state of the art in an area of technology bydescribing recent developments for readers who are not specialists in thetopics discussed. Written by individuals recognized as experts in the area, these articles provide key references to more definitive work and presentspecific details only to illustrate the technology. Purpose: to informthe general readership of recent advances in various areas of petroleumengineering. Summary. Project profitability analyses determine the impact of investmentson the investor's financial position. An investment screening criterion willidentify acceptable investment opportunities, which will enable the investor toundertake those projects that will provide the greatest increase in networth. Introduction To remain in business, it is necessary to invest primarily in projects thatare expected to generate funds in excess of the investment over a period oftime-i.e.. show a profit. This was qualified by the word "primarily," becausefrom time to time it is necessary to undertake certain projects that are notexpected to show an obvious profit, but must be undertaken anyway for othercompelling reasons, such as safety, environmental, or legal. This paper willnot address these investments but will focus solely on investments made withthe expectation of a profit. This paper will be further limited to a discussionof profitability determination for investments to be made in oilfield-typeprojects. Obviously, not all investments made with a profit motivation will actuallyresult in a profit, because there are many unforeseen occurrences that cansubstantially reduce or even eliminate the anticipated income. The importantfact in making an evaluation before the expenditure, however, is that a profitis expected. The term "expected" will be used throughout to indicate astatistical outcome. Expected values for the particular evaluation reflect notonly what is most likely to happen, but also the best and worst outcome thatcould reasonably occur. Procedures used to evaluate the profit potential of investments have notalways been as detailed as those used today. Before the widespread use ofsophisticated calculators and computers, many rules of thumb were used in placeof more rigorous calculations. Such guidelines as limiting investment to agiven number of dollars per barrel of daily production, or a certain multipleof the annual income, or a specified dollar value for each barrel of oil in theground were widely used. Profit per barrel of reserves was commonly calculatedwith current costs and revenues. But as more rigorous methods were developed toevaluate investment opportunities, along with tools to make those calculationsquickly and accurately, such techniques have become widely used and accepted bythe petroleum industry. Undiscounted profit and undiscounted profit-to-investment ratio werecriteria used for many years to judge the desirability of investmentopportunities. While this obviously was an improvement over simple rules ofthumb, it ignored a very significant factortime-and its associated cost, thecost of the invested funds or what is usually called interest. Interest can bethought of as rent that must be paid to use the money and is a cost of doingbusiness as much as direct operating costs. This is obviously true whenborrowed funds are used, but is just as true when funds from any other sourceare used, because if they were not invested in the project being considered, they could earn interest elsewhere. The underiving principle in most investmentevaluation techniques in use today recognizes the time value of money, which isapplied by discounting future cash flows to present value at some particulardate. This gives meaning to the phrase "time is money." Purpose of Economic Analyses The purpose of an economic analysis is to determine the effect a certaininvestment will have on an individual's or company's financial position. Because the objective is to evaluate only the change of financial position thatwill result from a potential investment and not to determine the overallprofitability of the organization, the investment opportunity can be evaluatedalone. JPT P. 263^

Journal Articles

Journal:
Journal of Petroleum Technology

Publisher: Society of Petroleum Engineers (SPE)

*J Pet Technol*24 (01): 90–100.

Paper Number: SPE-2994-PA

Published: 01 January 1972

... to know where you are, but also how you got there, and where you may be going! Historical Introduction The

**time****value**of**money**has long been recognized, and the search for improved profitability criteria has been continuous, but**time**-related profitability criteria did not gain wide acceptance in the oil...
Abstract

The two predominant profitability criteria in general use today are Dollar Profit discounted at the firm's cost of money and Discounted Cash Flow Rate of Return. Of the two, the former is a generally satisfactory and reliable screening and ranking yardstick; Rate of Return, however, has serious shortcomings and should be used only with great caution, if at all. General Introduction By comparison with the engineering time, talent, and effort that are usually involved in an oil and gas venture, the profitability analysis of that venture is simple. Yet the process of profitability analysis holds a particular fascination for almost any engineer, for here is the payoff; here is where he finds out if it is "go" or "no go"; here is where there may be a new job, or no job, a commendation or a "too bad"; for it is uniquely the engineer who is supposed to produce the proposal, the recommendation to undertake a technical venture at a profit - and the bigger the profit, the better. Although a review of profitability usage shows that widely accepted profitability criteria have always had a basic conceptual simplicity in common, this is not to say that the preferred criterion has always been the same, or even remained the same for any great length of time. This paper is directed at the working petroleum engineer, who does not specialize in profitability analysis but who makes such analyses in the course of practicing his profession. That the reader is quite familiar with the subject is therefore assumed. There is a difficulty in presenting a review paper to a knowledgeable audienceit is all too easy merely, to "plow old ground," leaving the reader bored and no better informed than before. We hope to avoid this by NOT presenting yet another set of derivations of discounted cash flow rate of return, discounted value profit, cost of money, or any of the equations dealing with risk or uncertainty, or the statistical theory that underlies these concepts (these analyses can be found in the references). Rather we hope to provide a bridge whereby the profitability analysis provide a bridge whereby the profitability analysis experts, the nonexpert profitability analysis makers, and the decision makers who use profitability analysis can better understand one another's requirements. We also expect to place the present state of the art within its historical context because we believe it is useful not only to know where you are, but also how you got there, and where you may be going! Historical Introduction The time value of money has long been recognized, and the search for improved profitability criteria has been continuous, but time-related profitability criteria did not gain wide acceptance in the oil industry until the late 1950's. During the post-World War II development drilling boom, oil companies were producing some 20 percent net returns on net shareholder investment; money was available at 3 and 4 percent interest rates, and in all, management perhaps did not feel a compelling need for highly refined profitability criteria. profitability criteria. JPT P. 90

Journal Articles

Publisher: Society of Petroleum Engineers (SPE)

*SPE Res Eval & Eng*23 (04): 1251–1264.

Paper Number: SPE-201245-PA

Published: 12 November 2020

... in simulation studies, particularly the concepts of

**time****value**of**money**and oil‐price sensitivity. This has led to a knowledge gap in identifying optimal drawdown procedure and fracture spacing from numerical models. This study proposes a framework that integrates petroleum economics with simulation results...
Abstract

Summary Optimal spacing between fracture clusters has eluded reservoir and completions engineers since the inception of multistage hydraulic fracturing. Very small fracture spacing could result in fracture to fracture (intrawell) interference and a higher completion cost, whereas very large fracture spacing could lead to inefficient hydrocarbon recovery, which is detrimental to the well economics. Meramec Formation has moved to full‐field development, and multiple wells are put on production in a relatively short time. Depending on the desired economic metric, net present value (NPV), or rate of return (ROR), the magnitude of intrawell interference can be optimized by adjusting fracture spacing. For instance, if the objective is to maximize ROR, then tighter fracture spacing can be accepted. Furthermore, petroleum economics are often ignored in simulation studies, particularly the concepts of time value of money and oil‐price sensitivity. This has led to a knowledge gap in identifying optimal drawdown procedure and fracture spacing from numerical models. This study proposes a framework that integrates petroleum economics with simulation results to optimize a horizontal well from the Meramec Formation. On the basis of this framework, we identified optimal drawdown procedure and fracture spacing. Then, oil‐pricing sensitivity analysis was conducted to illustrate the effect of oil‐price volatility on design parameters. Moreover, this study investigates the relative contribution of reservoir and completions characteristics with regard to short‐ and long‐term well performance. These characteristics include drawdown management, fracture spacing, pressure‐dependent permeability, critical gas saturation, and petrophysical properties. Available geologic data were integrated to construct a geologic model that is used to history match a well from the Meramec Formation. The geologic model covers an area of 640 acres that encompasses a multistage hydraulically fractured horizontal well. The well is unique because it is unbounded and has more than 2 years of continuous production without being disturbed by offset operations. Findings suggest that the drawdown strategy (aggressive vs. conservative) has more effect on short‐term oil productivity than fracture spacing. Drawdown strategy even has more of an effect on short‐term oil recovery than does a 20% error in porosity, or water saturation. Furthermore, the profile of the producing‐gas/oil ratio (GOR) depends on completions efficiency, and it has been interpreted using linear‐flow theory.

Journal Articles

Journal:
Journal of Petroleum Technology

Publisher: Society of Petroleum Engineers (SPE)

*J Pet Technol*18 (08): 924–928.

Paper Number: SPE-1432-PA

Published: 01 August 1966

..., mostly those which have been used by financiers for several centuries. Although many different yardsticks have been proposed and used, all the better ones recognize the

**time****value**of**money**, which payout and the profit-to-investment ratio ignore. The most widely accepted yardstick for profitability seems...
Abstract

Petroleum technology has improved to the point that reasonably accurate forecasts can be made of the performance of waterflood projects and of the cash flows which will result. Increased reliance on the predictions of economic performance has been accompanied by application of the mathematics of investment to measure profitability of proposed waterfloods. The internal rate of return method is at present the most popular yardstick used in measuring profitability. This paper investigates the effect on profitability of deviations from predicted performance. Various types of changes in costs and income are postulated, and their effects studied. In general, profitability proves to be most sensitive to the amount of oil recovered, but the speed of recovery is almost as important. Further analysis demonstrates the merit of purchasing prospective waterflood acreage using overriding royalties rather than cash alone. Introduction Waterfloods are profitable, but expensive. Furthermore, a waterflooding company may invest large sums of money and continue operations for a year or more before early returns first signal success or failure of a venture. Therefore, a sound evaluation of the economic prospects of the flood is vital. Fortunately, years of experience and mountains of experimental and theoretical studies have enabled engineers to forecast performance of waterfloods with a reasonable degree of confidence. From these forecasts, predictions of costs and income can be made which allow management to establish the value of a flood prospect. Mother Nature is too stubborn to sustain all these forecast, and the actual performance of many floods diverges widely from predicted performance. How much these divergences affect the value of a flood is of serious interest to management, and is the subject of this paper. Measurement of Profitability First, we must answer the question: how does management measure the value of a project? Although companies may consider other factors, most often it is the profit to be derived from a project that determines its value. Profit is the reward to the company for efficient production of crude oil needed by the rest of the economy. Profitability refers to the value of this anticipated reward. But how is profitability measured? Which is better: to invest $500,000 in a flood which will return the investment plus a profit of $500,000 in 10 years, or to invest the same amount in another flood which will return the investment plus a profit of $350,000 in five years?The simplest yardstick used in this problem is payout The project which pays back the investment cost quicker is the better project. Another popular yardstick is the ratio of profit to investment. Both yardsticks are still in use, but evaluators agree that they are too coarse to screen out the best projects from the many complex, competing proposals presented to most companies. Particularly in the last dozen years, industry has begun to apply more sophisticated yardsticks, mostly those which have been used by financiers for several centuries. Although many different yardsticks have been proposed and used, all the better ones recognize the time value of money, which payout and the profit-to-investment ratio ignore. The most widely accepted yardstick for profitability seems to be the internal rate of return. Many companies, however, prefer some other measure of profitability which, unlike internal rate of return, gives consideration to the value of money to that particular company (Profitability Index, net present worth, appreciation rate of equity, etc.). In many ways, these latter indices are more trustworthy. For the purposes of this paper. any of the preferred yardsticks is adequate. Since rate of return seems to be more universally understood and used, it will be utilized for our comparisons. Rate of return may be defined as that interest rate which, when used to discount future cash revenue, will cause the net present worth of the future cash revenue (income less operating expense) to equal the capital investment. JPT P. 924ˆ

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020

Paper Number: SPE-203067-MS

..., an investment income analysis model, not taking into account the

**time****value**of**money**, was derived for TSC oilfield development projects. The well density**values**corresponding to the maximum and zero governmentWs profit were defined as government economic reasonable well density and government economic limit...
Abstract

This paper developed the method and strategies to optimize well density for oilfield development projects in Technical Service Contract (TSC) framework. The main TSC terms, including plateau production, capital investment, remuneration fee, etc., were summarized as the basis of well density optimization study. 8 calculation methods were recommended to estimate the technical reasonable well density which is fit for the plateau production requirements. Incorporating with the Shelkachov equation, which reveals the relationship between ultimate oil recovery factor and well density, an investment income analysis model, not taking into account the time value of money, was derived for TSC oilfield development projects. The well density values corresponding to the maximum and zero governmentWs profit were defined as government economic reasonable well density and government economic limit well density respectively. The influence of well density on contractor's profit was further investigated. Finally, the proposed method and investment income analysis model were used in a specific oilfield of the Middle East, which shows that the contractor's profit monotonically decreases with the augment of well density S within a certain range. The strategies, including enhancing oil recovery through drilling more wells and integrated operation with oilfield service companies, are recommended to the leader contractor of this TSC project.

Proceedings Papers

Paper presented at the SPE/AAPG/SEG Unconventional Resources Technology Conference, July 23–25, 2018

Paper Number: URTEC-2902818-MS

..., and because of the

**time****value**of**money**. Therefore, production analysis should answer the questions, "how much will this well produce?" and "how quickly?" complex reservoir Barnett shale gas hindcast prediction Artificial Intelligence transient flow Haynesville machine learning Upstream Oil...
Abstract

Abstract In this work I attempt to characterize uncertainties in production forecasting. The analysis focuses on how decline analysis results, that depend on the production profile of older wells, change as the population ages. Also I investigate systematic and random errors that affect EURs. This work is a retrospective on production forecasting performed in the Marcellus, Fayetteville, Haynesville and Barnett shale gas resource plays. Publicly available and subscription-based production data on 34,000 shale gas wells were forecast multiple times over a six-year period. We perform a hindcasting analysis on these wells, where production has been forecast using a physics-based decline curve analysis (DCA) and other published approaches. This allows us to test the accuracy of the decline methods and assess reasons for errors in this analysis. I also review data quality and its effect on production forecasting. Using this analysis, we find that there are a number of systematic and random errors that affect ultimate recovery estimates. Production forecasts for wells in which the production has been back allocated from lease level to well level show regression to the mean over time. This has an effect on the errors associated with individual well forecasts in these fields. Also, fields where few wells have entered boundary-dominated flow (BDF) show higher uncertainty for field-wide production forecasts. A proper accounting for individual well and population uncertainties is necessary for sampling data and risk assessment. Understanding the sources and magnitudes of errors and uncertainties in EUR values for unconventional gas wells allows operators to account for these in determining economic outcomes and financial planning of wells. Introduction In order to perform resource assessments, how individual wells decline must be understood. The ultimate production for each well is important, but just as important is how much of that production occurs in the first few years of the life of the well. Early production is important because of the cash-flow aspect that allows further exploration, and because of the time value of money. Therefore, production analysis should answer the questions, "how much will this well produce?" and "how quickly?"

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the SPE Nigeria Annual International Conference and Exhibition, August 5–7, 2014

Paper Number: SPE-172437-MS

... for a fixed interest rate and internal rate of return. Thus, establishing the

**value**of the cash flow backs compared to the expenditures and the**time****value**of**money**become trivially algebraic formulated using a discount rate compatible with the average rate of return on equity. Average rate of return...
Abstract

The popular yardsticks for ranking ventures in order of their profitability, among others, are rate of return on investment and present value. This paper describes applications of polynomial algorithms for fast and efficient determination of present-day value of total profit for a fixed interest rate and internal rate of return. Thus, establishing the value of the cash flow backs compared to the expenditures and the time value of money become trivially algebraic formulated using a discount rate compatible with the average rate of return on equity. Average rate of return on investment based on predicted cash flow backs compared to force value of investment to balance value of cash-flow-back at some common reference time, the time of investment. This leads to another definition; the internal rate of return is the rate of interest that makes the present-day value of the total income equal to the capital investment. Emphasis is placed on the proper utilization of the results in development of realistic mathematical model and proper consideration of profitability in economic evaluation. Application of digital electronic computer simplifies the extremely cumbersome calculation in 3-step algorithm.

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the SPE Eastern Regional Meeting, September 13–15, 2016

Paper Number: SPE-184075-MS

... economic margin (WC ec – WC ult ) is large, well spacing has little effect on the final recovery (when water cut becomes equal to WC ec ). Thus, well spacing could be designed for the same

**value**of recovery by finding optimum number of wells for maximum return on investment using the**time**-**value**-of**money**...
Abstract

Theoretically, ultimate water cut, (WC ult ), defines well's maximum water production for uncontained oil pay underlain with water. However, in a real multi-well reservoir well's drainage area is contained by a no-flow boundary (NFB) that would control water coning, so: (1) the ultimate water cut concept needs to be qualified, and (2) related to the well spacing size. Moreover, a simple presently-used (WC ult ) formula derives from other simplifying assumptions ignoring the effects of non-radial inflow, production rate and aquifer size, so: (3) the formula needs to be verified. The study shows that in multi-well bottom-water reservoirs well production water cut would never stabilize (after initial rapid increase) but would continue increasing at slow rate dependent on the size of well's drainage area, i.e. well spacing size. There is a minimum well spacing size – correlated here with reservoir properties – above which water cut becomes practically stable at the value defined as pseudo WCult. The pseudo WCult formula is developed by considering all previously-ignored effects. Then, the formula is statistically verified in a variety of bottom-water reservoir systems using three-level parametric experimental design and sensitivity analysis of variance. It is found that most of the new physical effects are statistically insignificant so, in practical applications, the pseudo WC ult values can be computed from the conventional WCult formula for well spacing greater than the value defined by the minimum well spacing correlation. The pseudo WCult concept and value has potential practical use for well spacing design in the strong-bottom-water reservoirs with known value of the water cut economic limit, WC ec , determined for the breakeven (zero-profit) cost of daily production. When the WC economic margin (WC ec – WC ult ) is large, well spacing has little effect on the final recovery (when water cut becomes equal to WC ec ). Thus, well spacing could be designed for the same value of recovery by finding optimum number of wells for maximum return on investment using the time-value-of money (NPV) approach. However, when the WC economic margin is small or negative, reservoir development decision should also consider increase of final recovery for smaller well spacing.

Proceedings Papers

Publisher: Society of Petroleum Engineers (SPE)

Paper presented at the SPE Eastern Regional Meeting, September 13–15, 2016

Paper Number: SPE-184045-MS

... stimulated reservoir volume (SRV) as possible, while taking advantage of

**time****value**of**money**. However, it must be far enough to minimize fracture interference (well to well interference and frac hits) and over-capitalization in a field development. Well spacing is impacted by many factors. The most important...
Abstract

Well spacing is one of the biggest decisions in a field development in unconventional shale plays. Not having optimized well spacing will either cost the operators additional capital or increase potential for unearned revenue. Well spacing must be close enough to contact as much stimulated reservoir volume (SRV) as possible, while taking advantage of time value of money. However, it must be far enough to minimize fracture interference (well to well interference and frac hits) and over-capitalization in a field development. Well spacing is impacted by many factors. The most important parameters requiring more study are matrix permeability, fracture half-length, dimensionless fracture conductivity (impacted by completions design), reservoir properties, capital expenditure, operating costs, and gas pricing. Deep dry Utica/Point Pleasant Shale is a new resource with limited data. The optimum well spacing in deep dry Utica is yet to be determined. This paper goes through a practical workflow that can be used to estimate the optimum well spacing based on various forecasts obtained from various half-length, permeability, and dimensionless fracture conductivity assumptions using hybrid or numerical models. In addition, a sensitivity analysis will be performed on the impact of gas pricing, capital expenditure, OPEX, permeability, and conductivity on the optimum spacing design selection. To create long term value for the shareholders, well spacing must be selected based on NPV. Production volumes could be important to the strategic development of a company, but the single economic parameter that creates long term value for the shareholders of a company is NPV. Therefore, NPV is used to optimize well spacing in this analysis. A case study from a successful deep dry Utica well located in Westmoreland County, PA will also be reviewed and presented as part of the workflow in this paper.

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