Abstract Three Pump Intake Pressure (PIP) calculation methods available for sucker rod lifted wells are discussed in detail in this paper. The values of PIP obtained from Acoustic Fluid level measurements, in wells with moderate pump submergence, yield PIP estimates that agree with those from pump fluid load analysis. If PIPs determined using these methods do not agree, then the operator can reduce the error by using the techniques discussed to make adjustments to certain parameters affecting the fluid load. Field data for a significant group of wells are used to compare the PIP results of the three methods. The results show that the PIP computed using the maximum and minimum pump card loads usually calculates too low of a PIP, while the PIP computed using the valve test loads are usually too high. Data processing techniques for improving the quality of the results from dynamometer data are presented. The pros and cons of using each method are discussed. Introduction Downhole pump submergence is defined as the amount (height) of liquid that exists above the pump intake. Since the early times of oilfield pumping pump submergence has been the parameter most used for monitoring and troubleshooting well operation. Acoustic determination of the depth to the liquid in the wellbore was introduced in the 1930s by C.P. Walker who also outlined graphical methods to obtain the pressure distribution in the well (1,2,3) . The advent of digital data acquisition and processing provided the tools to routinely convert fluid level measurements to estimates of downhole pressure distribution in the wellbore 4 . Today, pump submergence is easily converted to pressure at the depth of the pump intake. Figure 1 shows schematically the wellbore configuration and pressure distribution that exists in a well producing by means of a downhole pump means regardless of the type of artificial lift system employed. The measured depth to the fluid level is determined by acquiring and processing an acoustic signal round trip travel in the casing-tubing annulus. The casing-head pressure is measured and is used to compute the pressure at the bottom of the annular gas column using the gas properties and the geothermal temperature profile. Then the pressure at the depth of the pump intake is computed using the gradient of the annular fluid below the gas/liquid interface. The Pump Intake Pressure (PIP) determined acoustically is the pressure in the casing-tubing annulus at the depth specified as the pump intake. Depending on the configuration of the piping installed below the pump (strainer, gas anchor, mud joint, etc) this PIP may or may not be equal to the pressure at the actual pump intake but in general this value is considered to be equal to the pump intake pressure. In rod pumping, the measurement of pump rod load as a function of plunger position was first introduced by Gilbert's development of a mechanical downhole dynagraph that was installed at the bottom of the rod string and just above the pump plunger 5 .

Abstract A numerical nonisothermal two-phase wellbore model is developed to simulate downward flow of a steam and water mixture in the wellbore. This model entails simultaneous solution of coupled mass and momentum conservation equations inside the wellbore with an energy conservation equation for the fluids within the wellbore, surrounding medium, and formation. A new drift-flux model that accounts for slip between the phases inside the wellbore is employed. In addition, a two-dimensional implicit scheme that allows for heat transfer in both the axial and radial directions in the formation is developed. Furthermore, a rigorous nonlinear temperature- and depth-dependent overall heat transfer coefficient is implemented. The model predictions are validated against real field data and other available models. The model is useful for designing well completion and accurately computing the wellbore/formation heat transfer, which is very important for estimating oil recovery by using steam injection. Introduction Modeling of steam injection wells for continuous estimation of pressure, temperature, and different phase velocities and densities as functions of depth and time is crucial for well design, steam injection projects planning and data gathering for continuous reservoir management and real time well monitoring. Once steam is injected in the well, both pressure and temperature of the injected steam and accordingly the densities of water and steam phases will change. These changes are due to the heat exchange between the steam and cold formation surrounding the well, the friction between the steam and inner tubing surface and the change of the hydrostatic pressure with respect to depth,. More importantly, the injected steam quality will drop due to the heat loss from the wellbore system towards the cold formation. The steam quality in the formation can be much worse than that in the wellhead because of an improper wellbore design, no tubular insulation, and/or the deep well location. The multiphase nature of the flow inside the wellbore, the complex heat transfer mechanisms between the wellbore and the surrounding medium, and the unsteady state nature of the flow and transport processes make the entire system intricately coupled and extremely difficult to solve. Numerous investigators have worked on the modeling of both injection and production wells. One of the first papers goes back to Ramey (1) in 1962, which has been referred to by many subsequent works modeling the wellbore heat loss and pressure drop. In that paper, the author simplified the heat balance equation to solve it analytically. The steady-state flow of incompressible single phase, with fixed fluid and formation properties with respect to depth and temperature, was analyzed. A simple procedure was presented to couple the steady-state heat loss of the wellbore fluid with a transient heat flow in the formation via an overall heat transfer coefficient. Moreover, it was assumed that the overall heat transfer coefficient was independent of depth, and the frictional loss and kinetic energy effect were neglected. In 1965, Satter (2) improved Ramey's analytical model by considering a depth-dependent overall heat transfer coefficient and phase- and temperature-dependent fluid properties.

Abstract Analysis of production data for characterization of reservoirs is becoming more popular. Sophisticated tools and methodologies exist to extract permeability, completion effectiveness and pore volume from production data (rates and flowing pressures). Often, in practice, these are the only tools available, especially in the case of low permeability reservoirs where it is not practical to conduct buildup tests. Production data, though plentiful, can be of poor quality because of operational problems, or changes in operating conditions, which are usually not documented (re-completions, tubing change-outs, compression, liquid loading, pressure or rate averaging). If this poor quality or inconsistent data is not recognized as such, it can easily be misinterpreted as being a reservoir issue rather than the operating problem that it is. For example, liquid loading, if not recognized, may be misinterpreted as interwell interference or reservoir depletion. In this paper, we review many of the operating problems we have observed in practice, and we discuss ways and patterns for recognizing them as operating issues rather than reservoir phenomena. Diagnosis of production data quality is a critical and necessary step that must precede any interpretation of production data. Recognition of inconsistent data is not always an easy task, and requires a lot of experience. The diagnostics presented in this paper will help the engineer in recognizing these problems, and potentially avoiding misinterpretation of the data. Introduction The analysis of production data to determine reservoir characteristics, completion effectiveness and hydrocarbons-inplace is becoming more and more prevalent. The methods of analysis have been documented and verified in numerous publications [1–7]. The concepts underlying modern production data analysis are the same as pressure transient analysis. Even though both these domains use the same underlying theory of fluid flow through porous media and can determine the same variables (permeability, skin, reservoir size), it should not be assumed that they can replace each other. Pressure transient analysis and production data analysis should be viewed as complimentary and not substitutes for each other. Pressure transient analysis deals mostly with "high frequency/high resolution" shut-in data while production data analysis deals with "low frequency/low resolution" flowing data. This, in itself, presents significant differences in data quality and interpretations. Like all mathematical solutions, the production data analysis methods are subject to numerous assumptions, which often can be justified. In this case, if the data are complete, consistent and of good quality, meaningful results can be obtained. However, if the quality of the data is questionable, then the production data analysis methods should be used with caution. In this case, the analyst's ability to filter out the bad data and extract the true reservoir signal becomes extremely important. As mentioned by Anderson et al. [8], blind application of production data analysis methods without consideration of data quality issues can lead to misinterpretation of the reservoir characteristics. An analyst, who is not experienced in recognizing such inconsistencies, can obtain an answer that appears to be mathematically correct yet be completely wrong because of using "bad data" for analysis.

Abstract Underbalanced drilling (UBD) is one of the most widely used technologies preferred in depleted and/or low pressured formations. In order to achieve underbalanced conditions, drilling fluids are usually gasified. Major drilling fluids preferred during UBD are pure gas, gas-liquid mixtures, foams, etc. This study is focused on gas-liquid mixtures. As the gas is introduced, the behavior of the drilling fluid becomes hard to explain due to many reasons. First of all, gas is compressible and physical properties of gas are very sensitive to changes in pressure and temperature. Second, a multiphase flow phenomenon arises. When there is multiphase flow, flow patterns should be considered. It is known that, there is a difficulty to predict hydraulic behavior of gas-liquid mixtures due to this flow pattern dependence. During a drilling operation, one of the parameters that should be well considered is hole cleaning. Hole cleaning is a challenging task even for a single phase drilling fluid. Moreover, there is still a lack of information how the cuttings are transported when gas-liquid mixtures are used as drilling fluids. Flow rate optimization during UBD operations for liquid and gas phases are usually conducted based on formation pressures only. However, only considering this criteria alone as the optimization objective is misleading and may cause serious problems during the drilling operation. In this study, gas and liquid flow rates during UBD operations are conducted not only based on formation pressures, but also based on effective hole cleaning. It is assumed that liquid phase is the major contributor for cuttings transport, and gas phase is only influencing the bottom hole pressure. A mechanistic model is introduced for estimating the hydraulic behavior of gas-liquid mixture drilling fluids under different flow patterns. Based on the bottom hole pressure and effective hole cleaning point of view, an algorithm is proposed for estimation the optimum required flow rates for liquid and gas phases based on the introduced mechanistic model. Also, the model predicts the required backpressure that has to be applied. Introduction Underbalanced drilling operations are increasingly applied, especially when new wells are required at depleted reservoirs in order to conduct enhanced oil recovery techniques or secondary recovery applications. Usually, gas-liquid mixture fluids are preferred for applying underbalanced techniques. However, one of the main problems for applying underbalanced drilling techniques is te selection of proper liquid and gas volumetric flow rates. Generally, these rates are selected based on the formation pressure, i.e., at static conditions, the hydrostatic pressure of the mixture is selected to handle the formation pressure. But, in such a case, at dynamic conditions, bottomhole pressure may exceed formation pressure, and the advantages of underbalanced conditions are missed. If the dynamic conditions are considered for selecting the liquid-gas rates, this time at static conditions, bottomhole pressure may be too low when compared with formation pressure, and formation fluids may intrude into the wellbore. Therefore, it is a better option to keep the bottomhole pressure constant and equal to formation pressure for all times, i.e., static and dynamic conditions.

Abstract The objective of this study is to develop an analytical model to calculate hydrate recovery and rate of gas generation when a hydrate-capped gas reservoir is produced at a constant bottomhole pressure. A similar model has been developed in the past for constant rate production. Such models are useful, when large number of sensitivity studies are necessary to evaluate the uncertainty in reservoir parameters and only limited specific properties of a hydrate reservoir are available. In this work, a tank-type material balance equation is considered. This is combined with the solution for the temperature of the hydrate cap to obtain the rate of gas generation during the period of constant bottomhole pressure production from a hydrate-capped gas reservoir. A numerical solution was used to validate the assumptions made to develop the analytical model; this numerical model relaxes some of these assumptions. The role of hydrate in improving the productivity and extending the life of hydrate-capped gas reservoir is demonstrated. The results show that the overlying hydrates can have a significant effect on improving the productivity of the underlying gas reservoir and increasing the reserve. Scope of the Study In this study we develop an analytical model to calculate hydrate recovery and rate of gas generation when gas is produced at a constant bottomhole pressure and decomposition occurs throughout the hydrate cap. For this purpose, a volumetric material balance equation is developed. The solution for the temperature of the hydrate cap is combined with the tank-type material balance equation and is solved for the rate of gas generation during the period of constant bottomhole pressure production from a hydrate-capped gas reservoir. In the following, after presenting the analytical modeling of the process, we perform a sensitivity study to investigate the effect of various reservoir parameters on reservoir performance, including the importance of porosity, thickness of hydrate zone, thermal conductivity and well bottomhole pressure. Analytical Model In order to obtain an analytical model to predict the recoverability of hydrate during constant bottomhole pressure production from a hydrate-capped gas reservoir, we assumed decomposition of hydrate occurs simultaneously throughout the hydrate layer. Four equations are used to develop the analytical model for predicting the behavior of the hydrate-capped gas reservoir during the period of constant bottomhole pressure production: Material balance equation Energy balance equation Hydrate decomposition model Inflow performance equation In the following, first the above mentioned equations are explained, and then the mathematical modeling of the process leading to the analytical model is presented. 1) Material balance equation: It is assumed that the pressure and temperature within the reservoir are instantaneously uniform; a depletion type material balance model can be used to predict the average reservoir pressure of the hydrate-capped gas reservoir. The simplified form of this equation for a volumetric hydrate-capped gas reservoir can be written as (Gerami et al., 2006): Equation (1) (Available in full paper) In the above equation, G p and G g are cumulative gas production and generation, respectively, and G f is the initial free gas-inplace.

Abstract One of the key duties of a reservoir engineer is extracting information and knowledge about flow patterns and reservoir architecture. This paper will address the combination of empirical statistical analysis techniques with conventional field surveillance analysis and analytical forecasts to determine reservoir fluid flows. Generating these mental reservoir models will greatly assist in determining upside potential for oil fields. Analyzing production and injection data to formulate production forecasts and to understand oil field mechanics is a critical skill that petroleum engineers need. Typically, reservoir engineers use decline analysis and analytical models to understand base case forecasts. Engineers commonly use analytical and analogy techniques to determine upside potential on a field wide basis. To forecast upside potential we need to understand what the remaining oil in place (ROIP) is, where this ROIP is located, and the conditions that the ROIP is in (pressures, saturations, etc). In order to formulate an answer to the above questions it is crucial to understand individual producer-injector connections. The methodology explored in this paper uses empirical statistical analysis as well as common waterflood surveillance techniques and analytical methods to develop a mental model of fluid flow in reservoirs. All cases used are field cases. Empirical statistical approaches, although innovative in their inception, have to be tempered with classical reservoir surveillance multiphase techniques to yield practical answers and eliminate false correlations. Some of the key conclusions are; Purely empirical statistical approaches such as Spearman ranking are very useful in identifying possible flow paths. The degree of connectivity or communication is a function of waterflood maturity and primary depletion. Therefore classical analytical techniques should be used to determine when statistical approaches are used. Analogy or analytical models should be applied to check the physicality of the connectivity and more definitely identify flow paths. Using production data to identify trends enhances the flow simulation understanding. Introduction The paper's objective is to gain preliminary understanding of communication amongst wells, using only production data and translate that communication knowledge into geology and reservoir engineering concepts. Reservoir surveillance on existing waterfloods and any EOR injection process is key to optimizing oil recovery and determining production potential. Geological studies alone cannot conclusively quantify the reserve and oil rate increases that can be achieved by optimizing existing waterfloods or EOR injection process. The usual way to incorporate geological knowledge in understanding reservoir flow is flow simulation. But before flow simulation the authors strongly recommend to do surveillance techniques to build mental models of the reservoir flow. There are six basic interrelated questions must be addressed in any EOR/waterflow surveillance and monitoring programs; What is the original oil in place (OOIP)? Where is the current OIP? What is the remaining oil in place (ROIP)? How is it distributed and what condition is it in? What are the factors that limit recovery? How can oil recovery be improved/ what is the production potential? Can oil rates and reserves be economically increased? Previous papers and talks have focused on determining the quantity of ROIP at a field or unit basis.

Abstract Decline analysis using Arp's equations is the primary empirical method used in the petroleum industry for estimating future reserve recovery and generating production forecasts. The development of tight gas and in particular shale gas reservoirs as important new sources of gas production has highlighted a concern with the hyperbolic form. That is, the expected ultimate reserve (EUR) is highly dependent on the choice of ‘b’ value. Recent work by Ilk et al has proposed a new decline formulation called the "power law loss-ratio" that they claim is more general and robust than Arps. Essentially, the power law loss-ratio predicts that ‘b’ changes over a well's producing life and the ‘D’ and ‘b’ values can be replaced with more predictable parameters called ‘D ∞ ’, ‘Di’, and ‘n’. The purpose of this paper is to test the applicability of the power law loss-ratio method with readily available public data. Several wells were analyzed using Arps hyperbolic decline and the power law loss-ratio method. The results of each will be presented along with a comparison of the estimates of ultimate recoverable reserves. Introduction Significant tight gas has been produced over the past few decades in Alberta. In 2005 it was estimated that tight gas accounted for 30% of the output from the WCSB (7) . There is an estimated 575 Tcf of tight gas in Western Canadian reservoirs. Shale gas production is also gaining interest, with plays with a resource potential of 261 Tcf having already been discovered. With such valuable sources of gas available, it becomes important to be able to predict reserves using reliable methods. For many decades, the main tool used for analysis has been the Arps decline analysis method. The purpose of this work is to demonstrate the practical application of a modified Arps method: the power law exponential method of decline analysis. Decline Analysis Decline analysis is a reservoir engineering technique that has been around for more than a century. The method has not significantly changed since the refined form proposed by J.J. Arps in 1945. Owing to its simplicity and reliability, it has been a popular method to forecast production and estimate reserves. The purpose of decline analysis is to forecast the cumulative production of a well up to the point it reaches a defined abandonment criteria. The amount produced is known as its expected ultimate recovery (EUR). There are two forms of the Arps equation that are commonly used to model rate decline. The exponential form is usually used for single phase liquid production or high pressure gas wells: Equation (1) (Available in full paper) The hyperbolic form is usually more appropriate for typical gas wells: Equation (2) (Available in full paper) Although Arps should be limited to the boundary-dominated flow portion of the production history where operating conditions (back-pressure) are relatively constant, practitioners regulary attempt to utilize Arps in the transient flow region. The transient period for a tight or shale gas well is often much longer than for a typical gas well.

Abstract The annular frictional performance of non-Newtonian fluids is one of the major considerations during developing hydraulic programs for drilling operations. Proper estimation of the frictional pressure losses become more critical while determining hydraulic horsepower requirements and selection of proper mud pump systems, and foresee any serious problems that may occur regarding with hydraulics during drilling operations. Since the rheological behavior of the non- Newtonian fluids has already been challenging, it becomes even more complicated during pipe rotation, especially in eccentric wellbores. In many cases, significant differences are observed when theoretical calculations and measurements for pressure losses are compared. This study aims to develop correction factors for determining the frictional pressure losses accurately in eccentric annulus for non-Newtonian fluids including the effect of pipe rotation. Extensive experimental work has been conducted on METU-PETE Flow Loop for numerous non- Newtonian drilling fluids including KCl-polymer muds and PAC systems for different flow rates and pipe rotation speeds, and frictional pressure losses are recorded during each test. Rheological characteristics of the drilling fluids are determined using a rotational viscometer. Observations showed that, pipe rotation has a significant influence on frictional pressure loss, especially at lower flow rates. Up to a point, as the pipe rotation increases, the frictional pressure losses also increase. As the flow rates are increased, the effect of pipe rotation on frictional pressure losses diminishes. Also, after a certain pipe rotation speed, no additional contribution of pipe rotation on frictional pressure loss is observed. When the developed friction factors are used, there is a good agreement between the calculated and observed frictional pressure losses for any pipe rotation speed. Introduction Proper determination of the frictional pressure loss for a non- Newtonian fluid is a very challenging task during pipe rotation, especially in eccentric annuli. On the other hand, poor estimation of the frictional pressure loss may cause serious problems in selection of the mud pumps and determination of the hydraulic horsepower requirements. Therefore, it becomes more significant and essential to identify the frictional pressure loss of non-Newtonian fluids in an annulus with pipe rotation. A number of studies have been conducted to investigate the influence of pipe rotation on frictional pressure loss in eccentric and concentric annulus over the years. Delwiche et al. 1 and Marken et al. 2 investigated using real wells pipe rotation effects on pressure loss and found that frictional pressure loss increase if applying rotation to the inner cylinder in the annulus. In addition, Marken et al. 2 emphasize that the flow regime and pressure losses is affected combinations of pipe motion, eccentricities and temperature along the length of the annulus. McCann et al. 3 pointed out that pipe rotation speed and eccentricity strongly affect the pressure loss in narrow annuli. They observed that for power-law fluids, when the flow regime is turbulent, the pressure loss increases with increasing pipe rotation, and when the flow regime is laminar, pressure drop decreases with increasing pipe rotation. Hansen and Sterri 4 experimentally investigated the effect of rotation on the frictional pressure loss in an annulus.

Abstract The so-called induction period, the time delay between the initial exposure to oxygen of an oil or oil fraction and the start of rapid oxidation, was examined experimentally for the saturates fraction separated from a Lloydminster heavy oil. The observed kinetics could be explained by assuming that the saturates contained a small amount of naturally occurring oxidation inhibitors, which repressed the oxidation rates by rapidly consuming an essential intermediate in the reaction chain, but which were also gradually consumed in the process. This observation explains some of the complexity that has been seen in the oxidation rates that control combustion front development during in-situ combustion, and provides some added direction in the development of a comprehensive reaction model for this process. Introduction For enhanced oil recovery of heavy oil by in-situ combustion to be viable, it is essential that a high-temperature combustion front be established and maintained (1) . Unfortunately, the creation of a combustion front can be thwarted (or sometimes aided) by the reactions that occur at temperatures below those needed for combustion. This problem has stimulated interest among some oil producers for a prediction method that can define the conditions for stable field operations. Low-temperature oxidation (LTO) is chief among the troublesome reactions. During the initial ignition period of an in-situ combustion project, the temperature must pass through the low-temperature oxidation (LTO) region, and therefore the success of an ignition is strongly influenced by this group of reactions. Similarly, when a combustion front encounters conditions at which factors such as a low air flux or heat losses reduce the temperature so that high-temperature oxidation is weakened, the LTO rates may dictate whether or not a combustion front remains stable. LTO has been found to be complex, and efforts to model it (2,3) have needed much more than a single reaction with Arrhenius rate parameters. In addition, the behaviour of the saturates fraction of oils has been shown (3) to be starkly different from that of the other SARA fractions. One of the major differences between the oxidation of saturates and the other aromatic-type fractions is that the saturates, when separated from the other fractions, exhibit a prolonged period of apparent inactivity after which LTO becomes much more rapid. In the literature on the chemistry of air injection, this is normally called an "induction period". There are two commonly accepted explanations for an induction period. One explanation is that it reflects the time for some intermediate compound in an essential chain of reactions to build up to the concentration needed for it to affect oxidation rates significantly. The other explanation is that a period of low reaction rate will exist until certain compounds that act as scavengers of an essential free-radical intermediate are consumed by their action. The difference can be important. If the first explanation is true, then a new induction period will occur whenever oxygen supply is interrupted and the essential intermediate becomes consumed as it continues along its reaction path.

Abstract Traditional decline methods do not work for tight gas wells. A hyperbolic decline is often used for forecasting the production rate and estimating the expected ultimate recovery (EUR) of a gas well. This method is only valid when the well is in the Boundary-Dominated Flow (BDF) regime, and hyperbolic b-values are in the range of 0 to 1. However, most of the production data from tight gas reservoirs is in the transient flow regime and not in the BDF regime. This results in values of b bigger than 1, and a forecast which can significantly over-predict the reserves. The recently developed "power law exponential decline" method seems to be promising in predicting the production rate over both transient and BDF regimes. In this paper, we examine the applicability of the power law exponential decline for different cases. We evaluate its behavior during both the transient and boundary-dominated flow regimes, and specifically for linear and radial transient flow. In the BDF regime, we also study the effect of reservoir size on the decline parameters. We compare the power law exponential decline with the decline from analytical reservoir models, and we modify it accordingly. Furthermore, the sensitivity of the power law equation to any of its parameters is studied. The validity of the power law exponential decline in forecasting production in tight gas wells is tested using synthetic data. Introduction The production of tight gas is becoming commercially significant in North America, and forecasting the future deliverability of tight gas wells is critical to the quantification of reserves. There are two methods of analyzing production data, namely the traditional methods such as exponential or hyperbolic decline [1] , and the modern methods such as Blasingame, Agarwal and the Flowing Material Balance [–6] . The traditional methods are very popular, because they are very easy to use, and only require flow rate and time as inputs. They have served the "reserves evaluation" industry quite well for nearly 100 years. For conventional oil and gas wells, these simple methods are reasonably well behaved and their performance is well understood. However, for tight gas wells, they fail spectacularly, and typically significantly over-predict reserves. The modern methods, on the other hand, are more rigorous, more sophisticated and more reliable. They work well for both conventional and tight gas wells, but they are more complicated to use, and require the availability of bottom-hole flowing pressure in addition to flow rate and time. It is well known that the traditional methods should only be used with production data after Boundary-Dominated Flow (BDF) has been reached [7] . During transient flow, these methods do not apply, and usually result in an "apparent" hyperbolic exponent, b>1. If this value is used to forecast future production, it can significantly over-predict reserves [8] . Not withstanding this serious shortcoming, tight gas wells are commonly forecast using hyperbolic decline with b>1.

Abstract Well test analysis in naturally fractured reservoirs is generally based on the radial flow model. The radial flow model is however only applicable to purely homogeneous system and long time solution. It cannot provide complete formation analysis in a reservoir that exhibit anisotropy. This study therefore presents a new method of estimating permeability anisotropy in naturally fractured reservoirs. Maximum and minimum permeability are obtained in one well test. The maximum permeability is attributed to the large scale fractures in the system while the minimum permeability may be due to the small scale fractures orthogonal to the large scale fractures. In a situation where the fractures are orienting in one direction, the minimum permeability will reflect the matrix permeability. The type of flow path developed (narrow or wide flow path) can also be predicted. This is useful in predicting the direction of fluid flow. Application was made to four field examples, one of which was an interference test. The interference test was used as a validation process. The results obtained are in agreement with that of interference test method of analysis. Introduction Naturally fractured reservoirs are anisotropic systems whose flow characteristics depend on the fracture network. Their permeability variation is not only stratigraphic in nature, but is also caused by the fractures' distribution, orientation and permeability impairment within the fractures, caused by pressure solution. The reservoir becomes more complex when both the matrix and fracture exhibit anisotropy and have the capability to flow into the wellbore as in double permeability case. According to Nelson 1 , naturally fractured reservoirs can be divided into four categories. Type 1 Fractures provide the essential porosity and permeability. Type 2 Fractures provide the essential permeability while the matrix provides the essential porosity. Type 3 Fractures assist permeability in an already producible reservoir. The matrix already has good permeability. Type 4 Fractures provide no additional porosity or permeability, but create significant reservoir anisotropy (barriers) due to mineral filled. Previous studies have shown that the fractures distribution and their permeability depend on the stress anisotropy. According to Price 1 , the two perpendicular orientations of most regional fracture sets are rotated to basin shape. As most basins are elliptical, one orientation of the orthogonal pattern parallels the long axis of the basin and the other parallel the short axes of the basin. High permeability fracture network will align with the maximum stress direction. Figure 1 is an example of such naturally fractured reservoir in offshore Abu Dhabi 2 . According to Gouth 2 , the interpretation of 3D seismic shows numerous low displacement NW-SE striking normal faults cutting the reservoir (Figure 1). These faults are oriented perpendicular to the dominant trend of the open fracture system and predate the formation of the open fractures. A second set of fractures is subparallel to the fault trends, but since they are described as mineralized, these fractures are assumed to be healed and have little effect on fluid flow. Thus the SW-NE trending open fractures formed the maximum permeability.

Abstract Gas hydrates are being considered as a future-alternate energy resource due to enormous quantities of natural gas deposition in hydrate form in the permafrost and offshore regions of the world. This study introduces an analytical numerical model for simulation of gas production by hydrate decomposition in porous media through depressurization process. Developments of several analytical and numerical models have been reported in the literature, however, mainly focused on decomposition processes. We coupled intrinsic kinetics of hydrate decomposition and heat transfer to analyze the production process. A commercial reservoir simulator was then used to construct a field scale model. A well is completed in the gas zone to follow the effect of depressurization in porous media and its effect on hydrate decomposition. Using the constructed analytical-numerical model a production strategy for a hydrate reservoir was designed. By use of this model the influence of different parameters related to formation properties, operating conditions, etc, on gas production may be predicted and evaluated. Introduction Natural gas hydrates in permafrost regions and offshore environments represents a potentially enormous supply of natural gas. This resource is expected to be an energy resource of the future. A portion of the gas hydrate reserves could help eliminate concerns of domestic energy shortage in the 21st century. Different estimations presented about the total energy reserves trapped in methane hydrates. The United States geological survey (kvenvoldsen, 1993) 1 estimated that the total amount of methane in gas hydrates around the world is approximately 7*10 5 trillion cubic feet (ft 3 ). According to Sassen 2 the resource potential of methane in hydrate exceeds the combined worldwide reserves of conventional oil and gas reservoirs, coal and oil shale. From technical view, the gas could be produced from the hydrate disociation by depressuriztion, thermal stimulation, inhibitor injection or a combination of these methods. The potential for gas production through different methods is still uncertain and under investigation. Developed models can be divided into two broad categories: analytical and numerical models. Analytical models are used for mechanistic studies and improve understanding of the process. Numerical models have smaller number of simplifying assumption, so they are more comprehensive. In this study, we focused on depressurizing method, where the pressure is decreased below the thermodynamic equilibrium pressure of hydrate. As previous studies mentioned, the heat transfer to the decomposing zone, intrinsic hydrate decomposition, and gas-water two phase flows are the three mechanisms involved in hydrate decomposition in porous media. Previous studies 3 showed the two first mechanisms are rate controlling in hydrate decomposition. So we used the analytical model to describe the heat transfer to the decomposing zone and intrinsic hydrate decomposition. Hoe and when after the production starts, the pressure decreases below the equilibrium pressure is a subject that studied more in this work. Analytical model Previous studies 3 showed that the rate of decomposition in controlled by the intrinsic kinetics of decomposition and the heat transfer to decomposing zone. So in this study these two processes are coupled to model the decomposition step.

Abstract In spite of their wide use in hydraulic fracturing and gravelpack operations, the complex flow behavior of surfactant-based fluids in straight tubing is least investigated. Accurate prediction of friction-pressure is essential for proper treatment design. Previous correlations from small tubings data and using simple power-law fluid model parameters alone do not scale-up to large tubing sizes for field application. The properties of one of the most popular surfactants, Aromox APA-T, are thoroughly investigated. It is a highlyactive surfactant used as gelling agent in aqueous and brine solutions. Commonly used surfactant concentrations (1.5, 2, 3, and 4% by vol.) are studied. Rheological and viscoelastic measurements are conducted using Bohlin rheometer. Flow tests are conducted using ?-, 1?-, 2?-, and 2?-in. tubings. The results show SB fluid exhibiting a non-Newtonian pseudo-plastic behavior. Fluid concentration and pipe shear have a significant effect on fluid elasticity. The conventional Fanning friction factor versus Reynolds number correlation is improved by including a new dimensionless group that accounts for both fluid elasticity and pipe diameter. A new definition of Deborah number is introduced. Thus, a new correlation for predicting friction factors of SB fluid in straight tubing is developed. The scale-up problem is thus alleviated with the present analysis and it provides more accurate friction-pressure estimates. Introduction In the petroleum industry processes, a variety of fluids are pumped through straight tubing during operations such as hydraulic fracturing, acidizing, wellbore cleanup, cementing and drilling which usually are executed under turbulent flow conditions. Turbulent flow regime is characterized by rapid fluctuations of velocity, pressure, and shear stress. The fluctuation is a function of time and position in the flow. They lead to development of high unsteady vortices and eddies which increase fluid resistance to flow. Therefore, high friction pressure losses are encountered which limits their pumping capacity. Adding small amount of specific high molecular weight polymers known as "Drag Reducers" under turbulent pipe flow condition can drastically decrease friction pressure gradient and thus, increase pumping capacity. Surfactant, the newly developed fluid requires less energy to pump than more conventional polymer fluids, effectively reducing wellsite pump-horsepower requirements [1,2,3] . Surfactants offer numerous advantages over conventional polymers. As drag reducers, the entangled micelles have much more resistance to mechanical degradation. Also, after disruption, surfactant molecules can reconstruct themselves to recover their drag reducing ability once the shear stress returns below a critical value while in polymer molecules, the disruption is irreversible. As hydraulic fracturing fluids, surfactant based fluids are viscous, non-polymer, water based, and have low molecular weight. Therefore, they do not leave much residue in the formation. Furthermore, they alleviate the need of various additives conventionally used with polymers. They can be used as carrier fluids for either hydraulic fracturing or gravel pack application and can be prepared with a variety of fluids including fresh water, brines and produced water as long as there is no hydrocarbon contamination [4,5] . Flow data gathered using lab tubing size are conventionally used to develop friction factor correlations to predict friction pressure loss in larger tubing sizes.

Abstract Sand production from unconsolidated formations in oil and gas wells has been a world-wide challenge for the petroleum industry for many decades. The challenge is not merely to avoid or stop sand production, but to be able to maintain commercial well productivity after efforts to control sand are implemented. At the same time, the control method selected must be justified by a reasonable payback time of the investment cost. Produced sand is a major problem in many production situations since small amount of sand entrained in the produced fluid can result in significant erosion and erosion corrosion problems. Even in "sand free" or clean service situations where sand production rate is only a few pounds per day, erosion damage could be very severe at high production velocities. Sand erosion can also cause localized erosion damages to protective corrosion scales on pipe walls and result in accelerated erosion-corrosion damage. In a high velocity gas well sand erosion is a serious problem since it can erode holes in the pipe work in a very short time period 1 . Produced sand can result in serious damage to the reservoir, where in some cases the reservoir collapses as a result of the sand production. Again, this scenario is a costly experience for the operator who has to overhaul and complete the producing reservoir zone. In this paper, we will present the optimum procedures for calibrating ClampOn sand detector which will help us to detect sand production. Also, we will present the effect of water production and choke change in the sand detector response. Introduction Control of sand production is a major concern in Sun Gas Company's offshore Gulf of Mexico operations. Sonic sand detection systems now in service on several Sun operated production platforms provide effective, relatively low cost platforms provide an effective, relatively low cost method for maintaining optimum production rates while minimizing equipment erosion and well bore damage. A case history of field application on one Sun platform as well as the theoretical basis for the Sonic Sand Detector is presented 2 . The major advantage of using the ultrasonic sand detector to detect sand is that sand monitoring has moved forward from a level of production trend to actual quantification in real time. The detector quantifies sand beyond its initial limit of profiling. The principle adopted uses an iterative method to locate a considerable threshold in the sand signature logged. Raw signals, in energy/sec, were simulated to reflect true sand production by marking up the background noise value, with about 10% to achieve the true sand free level of the signals for sand rate calculation 3 . Some of the lessons learnt from the application of the DSP Sand Monitor are; a single sample from a shakeout (Wellhead Sample) may not represent the true sand characteristics of a well. Average sand reading from the monitor should not be expected to match a single value shake out. Successful use of monitor requires teamwork and coordination among petroleum engineers (PEs), Operators 4 .

Abstract The motion and shape of a liquid drop through another continuous liquid phase (conveying phase) in a vertical Hele- Shaw cell with different two different apertures were investigated experimentally. Two different liquid-liquid systems were tested. In all cases, the continuous phase was more viscous and wetted the bounding walls. In the capillarity-dominated region, the irregular shape of the discontinuous phase changed with time and distance, with much lower velocity than that of the conveying phase. In contrast to gas-liquid systems, the velocity of these stabilized elongated drops was 2.5 to almost 5 times higher than that of conveying liquid. Despite the similarities between flow in vertical and horizontal Hele-Shaw cell, the velocity of droplets in vertical fracture is different from that of horizontal fracture. A new correlation is derived from dimensionless analysis and the experimental data to predict the elongated drop velocity as a function of the dimensionless parameters governing the system. Introduction Two-phase flow in micro-fractures is fundamental to many different fields of advanced science and technology, such as chemical process engineering, bioengineering, medical and genetic engineering as well as petroleum engineering. For instance understanding the flow of two-phase fluids in near parallel gaps through fractured rocks has a significant effect on design of different recovery methods for naturally fractured reservoir. The flow pattern of two-phase immiscible flow in a fracture depends on the flow rates of the phases, the geometry, aperture, and roughness of the fracture, the flow properties of the phases, and interfacial tension between the phases. The flow patterns in a fracture are different from that in macro size rectangular ducts or pipes due to the small aperture, which can enhance capillary effects. The flow structure in the fracture affects the flow and transport through the surrounding porous matrix blocks. The slug flow pattern in a fracture, which occurs over a wide range of parameters, is frequently encountered in oil-wet fractured reservoirs during the immiscible displacement of viscous oil. It also occurs in natural gas reservoirs during displacement of water during gas production. In the case of a smooth-walled fracture, the slug shape can be regular elongated drops (or bubbles) flowing through the conveying phase. The elongated drops (or bubbles) can have a rounded leading edge and occupy a considerable portion of the gap with length of several times to several hundred times that of the gap. The behavior of single elongated drops (or bubbles) through a continuous liquid phase problem is as rich and complex as the viscous fingering problem6. The conditions corresponding to a swarm of the elongated drops can be inferred by considering the behavior of a single drop (bubble) and their conglomeration. The interaction of many drops or bubbles across the flow cross section can also be inferred from single drop or bubble dynamics. A firm understanding of the behavior of drop or bubble flow in a single fracture is prerequisite to build predictive models for flow in complex fracture systems.

Abstract In 2007, work was published on the predictability of hydrogen sulphide production in Athabasca SAGD projects. It was possible to predict the hydrogen sulphide production per unit volume of bitumen produced against steam zone temperature, by assuming pseudo-zero order kinetics, using the Arrhenius energy published by Strausz and his co-workers at the University of Alberta. An examination of field results for carbon dioxide production in Athabasca projects shows that the predictability of carbon dioxide is less simple. The carbon dioxide production is not erratic but goes through a distinct temperature minimum, an important result in view of the dependence of silica production in SAGD and scaling behaviour in facilities on carbon dioxide. Again, as for hydrogen sulphide production, it is possible to estimate carbon dioxide production by a simple graphical technique, which is shown. Partial explanations for the observed temperature minimum are offered. Introduction The production of acid gases in SAGD projects is a matter of some importance. A number of operational characteristics depend on the presence of carbon dioxide as produced via dissolution in produced water. It has been shown previously 1 that silica production is strongly dependent on dissolved carbon dioxide. There is likewise evidence that aggressive degassing of produced water has caused unwanted scales of silicate minerals, such as talc, chrysotile and tremolite, to be deposited in various parts of the facilities 2 . A simple production diagram for hydrogen sulphide in SAGD was recently reported by Thimm 3 . The hydrogen sulphide produced per unit bitumen could be described as a simple Arrhenius-type relationship with steam zone temperature, using an activation energy of 56220–65920 kJ/mole (13450 to 15770 kcal/mole). The assumption of pseudo-zero order kinetics yielded a smooth curve which fitted the field data for most SAGD projects in Athabasca satisfactorily. The behaviour for carbon dioxide was previously expected to be similar, with an Arrhenius activation energy of 17520 kJ/mole (4192 kcal/mole) 4 . Field Results The results from field measurements of carbon dioxide generation in Athabasca SAGD projects show a very different situation from that which might have been expected from the Strausz value of a single activation energy. Figure 1 shows an upper curve, which, owing to the low activation energy reported by Strausz from laboratory measurements, is almost straight. This curve was the line expected from use of the data by Strausz. The curve actually obtained in field measurements between 180 and 215 degree steam zone temperatures is the lower curve, with field data shown in bold triangles. Surprisingly, the true production curve appears to go through a distinct minimum at approximately 195 degrees Celsius. As with the corresponding hydrogen sulphide curve in Figure 2, a first estimate of anticipated carbon dioxide production per m 3 bitumen may be read off the graph. Since the true production curve seems to rejoin the Strausz curve (upper line), production values above 215 ° C may probably be read off the extrapolation of the Strausz curve. However, the reader is cautioned that few field data in this higher temperature range have been published.

Abstract From September 2006 to a August 2007, a proof of concept test of ET-DSP ™ (Electro-Thermal Dynamic Stripping Process) was completed by E-T Energy Ltd. A numerical simulation study was done prior to the field test to quantify performance metrics, such as the amount of water usage per m3 of produced oil, the energy input requirements, kW-hr/m3 of oil (i.e. an equivalent Steam Oil Ratio value), green house gas emissions, drilling performance, operating costs, and process facility design. Field performance met or exceeded expectations. The recovery factor was greater than 75%, the energy requirement per m3 of oil produced was 23% less than calculated and peak production rates were greater than expected. The water oil ratio was one with no green house gas emissions in heating the oil. An insignificant volume of sand was produced and the oil recovered had very little to no emulsions. A comparison of the data with theory reveals that not all the drive mechanisms were considered in the initial numerical simulation. One of the more significant is the contribution of associated gas. Albeit in relatively small amounts, the gas evolving from the bitumen with rising temperature displaced the bitumen from the pore volume and accelerated recovery from the production wells. Introduction Electrical-thermal heating of the Alberta oil sands has been studied since the early 1970's [1],[2],[7],[6],[8],[4]. Heat is created in the bitumen reservoir as electrical current passes through the connate water as depicted in Figure 1. At low frequency, the reservoir behaves like a resistor, and the conversion of electrical energy to heat is by ohmic losses. This paper compares data from a pilot test of the Electro- Thermal Dynamic Stripping Process, ET-DSP ™ process [4] with numerical simulation (details are published in reference [5]. Construction and operations of the test was carried out from September 2006 to August 2007. The objectives of the proof of concept are to: Determine the percent Recovery Factor, R o , Establish the Energy Oil Ratio (EOR), i.e., the kWh/bbl of produced bitumen. Determine the water consumption on a per barrel of produced bitumen, Water Oil Ratio m 3 /m 3 , (WOR), Confirm numerical simulation temperature predictions, And Develop equipment and facility design basis, well completions, operating procedures, and economic parameters for commercial development. Table 1 summarizes the comparison between numerical model predictions and results from the pilot test. The recovery factor achieved in the proof of concept was within the model prediction. The energy consumption was less than the model predicted by 23%. Converting the energy in terms of an equivalent Steam Oil Ratio, SOR e = 0.49, or a Net Energy Ratio (NER) of 30 times more energy produced in the bitumen than used to produce it. The ratio of water used per produced barrel of bitumen was predicted to be one; slightly less than one was achieved in the proof of concept. A comparison of the modeled and actual temperature response at observation well (OB05) is shown in Figure 2. OB05 is located approximately mid way between the electrode wells.

Abstract Currently in the oil industry, productivity equations for a single well are erroneously used in all reservoir systems, regardless of the interference effects on flow rates of different wells in the same drainage domain This paper presents steady state and pseudo-steady state productivity equations of a multiple wells system in an anisotropic circular or rectangular reservoir. Taking fully penetrating vertical wells as uniform line sinks, and solving square matrices of dimension n, where n is the number of wells, simple, accurate multiple wells productivity equations are obtained. The proposed equations which relate the production rate vector to the pressure drawdown vector provide fast analytical tools to evaluate the performance of multiple wells, which are located arbitrarily in an anisotropic circular or rectangular reservoir. This paper also gives equations for calculating skin factors of each well. It is concluded that, for a given number of wells, well pattern, reservoir boundary conditions, anisotropic permeabilities and skin factor have significant effects on single well productivity and total productivity of the multiple wells system. For a given multiple wells system, if the reservoir is under edge water drive, when producing time is sufficiently long, productivity equation based on the steady-state is required; for a closed-circular or rectangular reservoir, pseudo-steady-state productivity equation is applicable. Introduction Well productivity is one of primary concerns in field development and provides the basis for field development strategy. To determine the economical feasibility of drilling a well, petroleum engineers need reliable methods to estimate its expected productivity. Well productivity is often evaluated using the productivity index, which is defined as the production rate per unit pressure drawdown. We often relate the productivity evaluation to the long-time performance behavior of a well, that is, the behavior during pseudo-steady state or steady state flow. The steady state and pseudo-steady state productivity equations of a fully penetrating vertical well located at the center of a homogeneous, isotropic permeability circular reservoir are sufficiently familiar to petroleum engineers and can be found in any reservoir engineering book [1] . Lu and Tiab extended these well-known productivity equations for a fully penetrating vertical centered well in an isotropic circular reservoir to an off-center partially penetrating vertical well in an anisotropic circular cylinder reservoir [2] . Lu and Tiab also presented steady state and pseudo-steady state productivity equations for a vertical well in an anisotropic box-shaped reservoir [2,3] . The performance of multiple wells system has received attention in the last decade. Camacho-V, Galindo-N, and Prats gave a buildup solution in a system with multiple wells producing at constant wellbore pressures [4] . Umnuayponwiwat, Ozkan, and Raghavan presented equations of pressure transient behavior and inflow performance of multiple vertical and horizontal wells in closed systems [5] . Marhaendrajana and Blasingame presented a solution and associated analysis methodology to evaluate single well performance behavior in a multiple wells reservoir system [6] . Valko, Doublet and Blasingame presented pseudo-steady state productivity index for multiple wells producing from a closed rectangular reservoir [7] , however their equation is only applicable to isotropic reservoir, and an infinite series summation is included in their equation.

Abstract Sand production is a serious problem in unconsolidated sandstone, it's becomes more critical as operators follow more aggressive production strategies. A successful sand control or management needed to evaluate sand production probability, to quantify risk reduction, and to establish practical operational scheme for safe and optimum production. In this paper, focusing on the coupling between fluid flow and solid deformation, a consistent geometrical frame for sand prediction is established, which includes the capacity to predict sand production onset, sand quantities and sand production rates. Finite element method is used to solve the coupled governing equation system. Field data for sand production and enhanced oil production from Bohai Oilfield (Tianjin, China) were used to validate the model for the sand rate and sand production. Our studies indicate that the optimized pressure drawdown in unconsolidated sand be controlled by the following key physical parameters: rock strength; fluid viscosity; pressure drawdown build-up strategy and pressure disturbance. The simulation results relating cumulative sand production and sand production rate to these important variables are presented. The study suggests that the proposed model may be used to generate quantitative information for predicting sand production and optimizing pressure drawdown. This provides a tool for sand-management in exploiting the weakness of sanding-prone scenarios. Introduction Sand production occurs when the well fluid under high pumping rate dislodges a portion of the formation solids leading to a continuous flux of formation solids. Sand production compromises oil production; increases completion costs, and erodes casing, pipes and pumps or plugs the well if sufficient quantities are produced. Another important sanding process occurs in formation failure leading to the well bore instabilities, this is particularly serious for the unconsolidated sand reservoirs in Bohai oilfield (Tianjin, China). A high stress distribution, especially near a well and perforation tips, often induces local formation collapse. Such collapse region may spread with fluid flow and sand production process. These sanding effects are becoming more critical these days as operators are following more aggressive production schedules. However, the permeability in the wellbore vicinity is increased as a result of cleaning of formation sand. Sand production has been proven a most effective way to increase well productivity both in heavy oil and light oil reservoirs. Because of the drawbacks of classical sand control techniques and the risks involved in uncontrolled sand production, Sand management has been operating in Bohai oilfield to optimized production rates and well productivity. Sanding prediction model predicts the production condition, e.g. pressure drawdown, at which sand production occurs and how much sand will be produced (rate and duration). It will be shown latter that, the pressure gradient variable takes as the important double roles in eroding formation matrix and dragging solid grains. At the same time, the fluid pressure can enhance solid matrix instability tendency. It is critical for sand management decision-making on whether or not sand control should be used, or when to use sand control.

Abstract The SAGD pilot test in Liaohe oilfield of China is the first one conducted in the medium-deep extra heavy oil reservoir (650-800 m), using the combination of vertical injectors and horizontal producers. Temperature observation wells play the important role in the understanding of the pilot performance and optimization of the operation process. This paper will present the objectives, principle, interpretation and application of the temperature observation wells in the pilot area. The production problems were identified and solutions were sought to improve the SAGD performance, through the use of data obtained from the observation wells. Introduction This paper is the continuation of CIPC paper 2006–146 presented in 2006. That paper introduced the successful test of the SAGD pilot in a medium-deep extra heavy oil reservoir in China [1] . The pilot has been expanded to include 12 horizontal wells since the presentation of the last paper two years ago. The earlier two wells have reached a daily oil rate of over 100 t/d per well. The current recovery factor is about 27% and the anticipated ultimate recovery is over 60%. Compared with the Canadian SAGD projects, the reservoirs in Liaohe oil field of PetroChina resulted in two difficulties using the SAGD technologies: (1.) reservoir depth exceeds 500 meters (530-810 m) compared to 200–500 meters in Canadian SAGD projects [2] , the heat loss from the wellbore is relatively high and this increased the difficulty for injection and production facilities and (2.) the depletion by Cyclic Steam Stimulation (CSS) prior to SAGD application while majority of the Canadian SAGD projects are commenced in the original reservoir conditions. The current recovery factor by CSS in Liaohe is about 20%. Prior depletion by CSS complicates the conversion to SAGD applications and determination of operating parameters due to the altering in the distribution of the remaining oil saturation (Fig 1). To overcome the difficulties associated with the SAGD applications in this reservoir, Lioahe Oilfield Company has taken various measures including the combination of vertical injectors and horizontal producers. The horizontal producers are placed in the lower part of the reservoir between two rows of vertical injectors to maximize the access of remaining oil saturations. A steam separator has been used to achieve high quality steam injection to maintain a quality of over 75% into the reservoir sand face (vertical depth of the reservoir is about 790 m); an over-sized tubing pump has been applied to provide the adequate lift capacity for the producers (peak liquid rate of 500 m 3 /d per well and the wellhead temperature of 180 °C). The monitoring of reservoir temperature is most important for any thermal processes. The thermal couples are usually used in the thermal recovery process. However, it can not provide the continuous and on time measurements as required by SAGD temperature monitoring. A distributed fiber optical temperature sensor system has been developed in recent years to provide the distributed, continuous and multiple functioned optical temperature measurement system.