Abstract While diagnostic fracture injection tests (DFIT) data is relatively rare, pressure and flow rate data are widely collected for hydraulic fracture treatment stages in multiple transverse-fracture horizontal wells, both during pumping and during pressure falloff after the end of pumping. Recent papers have shown value in applying analysis developed for DFIT data to hydraulic fracture treatment falloff (HFTF) data. As is often the case with routine processing of large volumes of data, the time required for analyzing HFTF datasets for each of the treatment stages in a long horizontal well may be overly expensive in time and human resources. To address this issue, this paper applies machine learning techniques to standard HFTF pressure data, to produce data-driven mathematical models that estimate wellbore and perforation friction loss, near-wellbore tortuosity friction loss, and the instantaneous shut-in pressure (ISIP). The models are trained based on a small subset of hydraulic fracture treatment stages, data from for which is processed manually, to provide targets for model outputs. Model structure is based on multivariate statistical methods, including principal component regression (PCR) and partial least squares regression (PLSR). Comparison between state-by-stage friction losses and ISIP values estimated manually and those quantified by machine learning reveals good agreement and underscores the value of the machine learning approach as a practical tool for field application tasks, including well and pad completion design decisions related to perforating strategies, and fracture and well spacing.

Waterflood conformance is a significant problem in the West Sak field of Alaska. Re-assembling Pre-Formed Particle Gels (RPPG) have been used to treat Void Space Conduits (VSC) and repair the "short-circuited" waterflood. These VSC’s are typically formed by sand producing wormholes. Several dozen VSC solutions have been implemented since 2006, including molten wax, cement blends, and pre-formed particle gels. To date, all the solutions have been faced with various limitations due to the low reservoir temperature and poor sand consolidation. A good percentage of the pre-formed particle gel (PPG) solutions have been successful in sealing off VSCs, but often show limited longevity that can range from as little as several weeks to several years. An effort was undertaken to develop a product that would provide enhanced stability in the VSC and extend solution life beyond the current range. A cost-effective conformance solution was developed with increased mechanical strength through a re-crosslinking process known as RPPG. The goal of the RPPG solution is to provide a longer-term repair to a VSC and restore the primary water flood characteristics. This paper will present the results of the seventeen RPPG solutions that have been pumped between 2017 and 2019 in the West Sak field on the North Slope of Alaska. RPPG treatments have shown a 23% improvement over traditional PPG treatments at the economic payout during the field trial. There have been some significant learnings through this time period. The focus of this paper will be to review the VSC problem understanding and the reason for the RPPG product development, detail the evolution of RPPG job design over time and provide results and operational knowledge from the field trial efforts. The latest advancements in conformance engineering will be of interest to Reservoir and Production Engineers who are focused on supporting and optimizing conventional waterflooded assets, particularly when faced with conformance issues in an unconsolidated reservoir. In addition, the field results will be useful to those seeking to implement RPPG solutions in their area of operation.

Analysis of fracturing water flowback data from hydraulic fractures in unconventional reservoirs plays an important role in determining key fracture properties and predicting future well performance. Current flowback data analysis tools mostly rely on empirical correlations and/or simplified models. This paper presents a semi-analytical, multiphase solution that is applicable to the analysis of not only water flowback but early gas production data of multi-fractured horizontal gas wells. The proposed solution couples a Green's function-based analytical solution for gas flow in matrix with a finite-difference numerical solution for two-phase (gas and water) flow in fracture domain. The validity of proposed semi-analytical solution is verified against simulation results generated using commercial numerical simulators. Inverse analysis techniques are developed based on the proposed semi-analytical solution and presented in the form of type curves. Synthetic case studies show that the proposed type-curve methods can provide explicit and accurate estimation of fracture and reservoir properties, including fracture conductivity, and fracture pore volume. For all case tested, the proposed model is shown to provide accurate and consistent prediction of reservoir performance and estimations of fracture properties while maintaining the simplicity of explicit, iteration-free calculations.

Well interference has been historically investigated by pressure transient analysis, while it has shown that rate transient analysis has great potential in well interference diagnosis. However, the impact of complex fracture networks (CFN) on rate transient behavior of parent well and child well in unconventional reservoirs is still not clear. To further investigate, this paper develops an integrated approach combining pressure and rate transient analysis for well interference diagnosis considering CFN. To perform multi-well simulation considering CFN, non-intrusive embedded discrete fracture model approach was applied for coupling fracture with reservoir models. The impact of CFN including natural fractures and frac-hits on pressure and rate transient behavior in multi-well system was investigated. Obvious distinctions could be viewed for different kinds of CFN on diagnostic plots compared with single-well model. Due to the interference from surrounding producers, new flow regimes including compound linear flow and interference flow would occur on loglog plot. In general, the effect of natural fractures seems to be more evident than that of frac-hits. Blasingame plots could be categorized into different types based on various CFN patterns. Application of this integrated approach to demonstrates that it works well to characterize the well interference among different multi-fractured horizontal wells in a well pad. Better reservoir evaluation can be acquired based on the new features observed in the novel model, demonstrating the practicability of the proposed approach. The combination of pressure and rate transient analysis can reduce the uncertainty and improve the accuracy of the well interference interpretation based on both field pressure and rate data.

With the gradually increasing applications of fiber-optic distributed temperature sensors (DTS) in unconventional resources exploitation, academic researchers have developed general theoretical models for forward temperature simulation and inverse flow rate profiling during and after stimulation workover. However, there have been no enough field applications for the established theoretical models and some practical issues still exist such as different completion scenarios are still lack of consideration in current models. This paper presents a DTS flow profiling case for a horizontal multi-stage fractured well in tight gas reservoirs with open-hole packer completion scenarios by applying a newly improved theoretical model. In this paper, for the modeling part, we start with the semi-analytical wellbore-fracture-reservoir coupled flow/thermal model but improve it to consider open-hole packer completion scenario. Compared with the conventional cased, cemented and perforated completion style, the fracture initiation points in open-hole stimulated well are more effected by near wellbore in-situ stress field. Therefore, the open-hole packer completion possibly forms a two-fold flow regime. The formation fluid firstly flows through the fracture into the open-hole annular space between formation and the packer liner, then flow along the annular space until meet the frac port on the production pipe. The two-fold flow regime results in double temperature drops due to Joule-Thompson cooling effect. The original theoretical model is improved by adding a simulation sub-region representing open-hole annular which helps to understand the flow and heat transfer inside it. With the improved mathematical model, DTS monitoring data during a three-rate production test in a horizontal multi-stage fractured well in Erdos Basin of China was simulated and analyzed. The improved model with open-hole packer completion was applied and then the gas flow profiling was accomplished.

Systematic and comprehensive analysis of gas lift operations must include historical performance evaluation and heuristic diagnostics for identification of suboptimal performers. Reliable nodal analysis models are necessary to optimize the gas lift systems. Though some degree of automation is currently possible, this process still takes substantial effort and time. The work presented here is a streamlined, repeatable, and automated workflow to diagnose and optimize gas lift operation through analytics, reliable wellbore modeling and calibration that reduces the time from days to hours. The workflow is also very easily repeatable, which makes it very efficient to update when new data is available. The workflow combines the emerging data analytics efforts in the oil and gas industry along with traditional gas lift optimization guidelines to identify artificial lift-related key recovery obstacles and corresponding development plans. This novel combined approach proves the effectiveness and necessity of augmented artificial intelligence, and the case study of field analysis and execution further endorse the impact of such optimization workflow for gas lift assessment and operations. It builds from data-driven and engineering-based workflows that compute smart metrics and dashboards based on the historical well production and the gas lift systems performance. Several KPIs and metrics are utilized, some of which are industry standard while others are intuitively built exclusively for this workflow. In this paper, we present the results and challenges in applying this workflow to an offshore Middle East oilfield, with over 50 gas lift wells. As always with field data, several aspects of the data had to be addressed. Accuracy and relevancy of data was questionable. We developed several workflows to address the missing/incorrect data to ensure the robustness and credibility of the results from the workflow. Due to the practical implication of the analysis, stringent quality control and error margins were maintained throughout the analysis. No nodal analysis models were available, consequently models were built and calibrated as a part of this effort. Overall field and facility constraints were also incorporated to ensure results were achievable in the field. The optimized operational plan would yield an additional 15 to 20% gains over current production rate. Further benefits by upgrading the gas lift design are also quantified using the proposed workflow. The time required to construct, calibrate, and optimize around 50 wells was less than two weeks.

Flowback rate transient analysis (RTA) is a practical tool for characterizing hydraulic fracture (HF) properties. However, the accuracy of the interpreted results from flowback RTA is challenged by the complexity in two-phase flow in the hydraulic fracture and matrix system. Accordingly, we present a new semianalytical method to characterize HF attributes and dynamics using multi-phase flowback data for tight and ultratight (shale) oil wells. The proposed method includes a two-phase diagnostic plot, a fracture RTA approach for straight-line analysis, and a matrix model capable of characterizing water and oil flow. The RTA approach is based on fracture infinite acting linear flow (IALF) and boundary dominated flow (BDF) solutions, which treats HF as an open tank with a variable production rate at the well and the contribution of water and oil from matrix within the distance of investigation (DOI). The pressure-dependent fluid and geomechanical properties, such as permeability and porosity, are considered in the pseudotime defined in fracture and matrix to reduce the nonlinearity of the system. We tested the accuracy of the proposed method against numerical results obtained from commercial software and verified its applicability by analyzing the flowback and long-term production data from a field example in Eagle Ford shale. The validation results confirm that our method can closely calculate water and oil influx from matrix as well as the average pressure and saturation in the HF and matrix DOI. The accurate estimation of the initial fracture permeability and pore volume demonstrates the applicability of the proposed method in quantifying HF properties from two-phase flowback data exhibiting fracture IALF and BDF regimes. The analysis results show that the estimated initial fracture pore volume shows more accuracy than initial fracture permeability due to the different calculation sources in the straight-line analysis. In short, the proposed method is, to our best knowledge, the first RTA approach incorporating the two-phase water and oil influx from matrix into the inverse analysis of fracture properties and dynamics using straight-line analysis, instead of history matching

The authors have developed an algorithm that combines simple, proven, analytical work tools. The algorithm allows one to quickly update the potential, taking into account geological and technical factors, assess risks, estimate current recoverable reserves, incremental oil production, and economics for each well. The purpose of the work is to reduce routine labor costs when searching for and selecting wells, to rank the entire list of relevant candidates, to increase the share of successful operations, as well as to increase incremental oil production by accelerating well optimization with minimal risk. A pilot project helped to improve the success rate of optimization jobs from 75 to 89%, and increase specific incremental oil production by 57% in comparison with the previous year. The tool can also be used for auditing decisions as a retrospective.

This paper presents three sets of new integrative production decline type curves for the analysis of horizontal well production data in order to systematically estimate reservoir flowing capacity ( kh ), effective horizontal wellbore length and original oil/gas in place. In addition, diagnostics of dynamic flow regimes possible for the entire flow duration from early time transient to late time boundary dominated flow gives the proposed type curves unique value in field data analysis through using different idealized flow regimes as the reference systems. Comparing to the traditional classic type curves, these three sets of type curves offer more practical implemental strategy for well performance evaluation and reservoir formation characterization, resulting in less ambiguity in the outcome of data interpretation. The effects of horizontal wellbore length and reservoir geometry on the appearances and the characteristics of these three sets of new type curves are studied and documented. A detailed curve matching process has also been comprehensively developed to achieve systematically proper matching with field data using all of the three sets of type curves synchronously. To showcase this work in field application, the production dynamics of a gas field containing two vertical non-commingled units, each being produced by a horizontal well independently, is analyzed using the three sets of new type curves. With successful estimation of the kh and the effective horizontal wellbore length, it helps geologists and geophysicists locate the "sweet spot" with more confidence and offer the potential to extend the seismic response pattern to support further exploration activity in this geology unit. The outcome of this work helped identify the existence of an untapped gas reserve in the lower unit, thus to promote the potential of infill drill to enhance ultimate gas recovery.

A pressure deconvolution technique based on ridge regression with existing convolution features was explored and reinterpreted to frame a new optimization problem structure. We found a way to split the feature matrix into a deconvolution part and a smoothing part that handle each effect independently. The deconvolution part is comprised of a convolution matrix (Toeplitz matrix) for discrete-time convolution while the smoothing part is composed of a basis function of the impulse response. Hence, this formulation preserves linearity (a superposition of pressure solution) and the kernel for nonlinear mapping (e.g., polynomial kernel, radial basis function kernel, etc.) is effective only on the smoothing part (a basis function of impulse response). Importantly, the key idea of existing convolution feature is the modelling of the impulse response with a linear combination of a basis functions. For single-well pressure behavior, ridge regression often struggles with high-frequency measurements that contain multistage responses. An impulse response might share similar functional characteristics, for example wellbore storage and pseudosteady state are both linear responses but there is only one linear basis function in the ridge regression which cannot describe them both. In traditional well test interpretation, the engineer is typically focused on certain parts of the impulse response on a log-scale, to identify reservoir behavior (e.g., early-time for wellbore storage, transient-time for infinite acting radial flow, late-time for boundary effect, etc.). Analogously, a basis function could be formed from multiple pressure responses in each log-interval (inherent from a solution of the diffusion equation) then bridged together with a constraint on function value and its derivative at each interval boundary. This is the basic principle of spline regression that has more flexibility in terms of function expression. In addition, it also subsumes ridge regression with Laplacian regularization. For multiwell pressure behavior, additional basis functions are included to handle interference responses. Typically, the exponential integral is approximated with a logarithm function for single-well pressure response which is also one of the basis functions in previous convolution features. Nonetheless, interference pressure response is more subtle and its solution could not be easily approximated, which previously resulted in a poor fitting using earlier methods. By inspection of the convergent series of the exponential integral, its higher-order terms are associated with 1/ t m that can be easily included as a basis function to enhance the capability of the model and capture the detail of the interference test that is essential for multiwell problems. A full extension to multiwell problems is also presented with the additional derivative constraint for the impulse response and symmetry constraint. Finally, we can quantify the sensitivity of the deconvolution process using singular value decomposition (SVD) and Monte Carlo simulation (MCS). Using singular value decomposition, we could reveal the orthogonal basis of the feature matrix and its corresponding singular value that helped us identify the effectiveness of the basis functions as well as their susceptibility to noise of certain pattern. Nevertheless, singular value decomposition is only suitable for noisy pressure measurement problems without inequality constraint. Thus, Monte Carlo simulation is required for full quantification of noisy measurements in both pressure and flow rate. We can observe a propagation of error in measurement to a band in pressure prediction and pressure derivative of the impulse response. This study developed a more robust method for deconvolution of pressure measurements. In addition, the mathematical insights obtained in the study allow for a more general understanding of how the deconvolution problem can be deconstructed into its relevant parts – likely allowing for expanded capability of deconvolution algorithms in industrial practice.

This paper explores the results of Repsol Bolivia's successful implementation of a workflow-based solution for real-time production surveillance as part of a digital oilfield initiative on Margarita Field. We will examine the fundamental aspects of data integration across multiple disciplines in the asset and the impact generated when having all the needed information available to rule-based processes in the same environment. This project successfully incorporated the main aspects of the operations. The implementation complements Repsol's Digital Oilfield initiative, started in 2013, with hardware installations for automation of wells, plants and other operational equipment. This paper will discuss the value of an integrated platform (data-processes-people) and the impact on the decision-making process. Margarita Field produces from ten high-volume gas wells that yield 30% of the gas production in Bolivia. This project targeted real-time well integrity, and operational monitoring to ensure stable production levels while automating a broad suite of best practices to improve efficiency for engineers, avoid production deferments, and enhance safety. This paper details how to leverage data in real-time and fully benefit from it by applying smart engineering workflows designed to integrate modeling tools, data, and engineering best practices. Prior to this implementation, it was demonstrated that a significant portion of the asset engineers’ time was spent simply gathering data from multiple sources. The previously installed, field data automation and real-time feeds, generated significant analytical benefits. However, the increase in useful data was underutilized and limited by the existing spreadsheets. These activities were manual and error-prone, and routinely led to: data duplications, data inaccuracies, and, most importantly, to delayed or suboptimal decisions based on incomplete or inaccurate information. The new solution addresses these challenges by providing an integrated environment where engineers have all the information and workflows readily available and automatically executed. To ensure the workflow automation did not mask problems or simply automate error-prone outcomes, validation gates were established to help ensure the engineers that the results were robust and sufficiently checked for quality. Automated, system-based reporting, helped to eliminate weekly manual reporting efforts, support the QC, and eliminate man time previously required to support operational meetings and decisions. The workflows are designed to maintain evergreen models to support the asset surveillance process. "Live links" to all sources ensures data duplication is no longer an issue and helps to establish "one source of the truth". The workflow-based automation has brought the various, pre-existing, well, production network, and reservoir modeling tools "Online" so they can be incorporated into daily operational surveillance activities and decision-making.

The determination of well and reservoir parameters is paramount during exploration, appraisal of new reservoirs, and equally important during the development and production phases of a field. The interpretation of pressure transient-test data is one of the tools to obtain such parameters under dynamic conditions. Often this data is substantially influenced by non-reservoir factors such as gauge drift, adjacent noise due to natural or operational reasons, insufficient gauge resolution and dominant tidal effects. Any of these non-reservoir factors can significantly lead to a misleading interpretation of the formation. Rigorous vigilance against such occurrences is particularly important in designing deep transient well tests. The paper quantifies these effects. Obtaining strong, unequivocal reservoir responses in the pressure data are imperative in extracting the reservoir and well characteristics. Individual and convoluted effects of noise, drift, resolution, periodic tides have been looked into quantitatively to demonstrate the situations when the reservoir signal is too weak to make any meaningful characterization. Reservoir models have been utilized to develop quantitative criteria to describe the dominance and subsidence of the effects of noise, resolution, drift and periodic tides under different operating conditions. These criteria should guide test design so that the subsequent test can produce meaningful data. Depending on the amount of disruption caused in the measurements, there are situations when the test objective may not be achieved at all. Failure to create dominant reservoir responses results from insufficient signal-to-noise ratio due to the rate of production and the pressure drawdown. It is a function of formation, fluid properties or mechanical environment. A minimum rate of production for creating the required magnitude of signal-to-noise ratio must be achieved to interpret correctly the reservoir response. The paper provides guidelines to determine the minimum rate and drawdown needed to obtain the presence of deep heterogeneities or boundaries with a reasonable level of certainty. If a test is run with a rate lower than the minimum value, for example, the data will be biased by other hardware or natural factors, unrelated to the reservoir response. Examples are also presented with artifacts of non-reservoir effects to show how misleading characteristics of the reservoir and the well can be deduced with such distorted data. This study establishes cause-effect relationships due to certain non-reservoir factors so that engineers can select their hardware, choose the methods and timings to mitigate the associated undesirable effects. Such a practical guide to select the most suitable transient test will rightfully fill in its place in the literature. The methodology applies equally to wireline testing operations, deep transient testing, drill-stem testing and production testing.

Hydraulic fracturing rate and pressure data are interrelated signals and can be subjected to signal processing techniques. The energy of a range of frequency band can be computed from the wavelet transform, which is a powerful technique in signal processing. The signal energies of the rate (cause) and pressure (effect) are used to detect the fracture events in time, such as height growth, screen-out, and hydraulic fracture-natural fracture interactions. The objective of this study is to relate the signal energies obtained from the wavelet analysis to the real physical phenomena of fracturing propagation events during injection. With this technique, the fluid injection during hydraulic fracturing process may be monitored in real-time for early diagnosis and to take preventive steps during the fracturing treatment Wavelet transform decomposes a signal into various levels of frequency components. The transform can be repeatedly applied to obtain a multiresolution analysis of the signal. Such repeated application of the wavelet transform yields the signal detail coefficients at each decomposition level, where each level represents a band of frequency. Using this approach, the pressure and rate signals from hydraulic fracturing were decomposed. Then, the pressure and rate signals energies at each frequency band were computed and compared to using energy density plots (EDP). Since wavelet transform preserves the time localization, all events on the EDP are obtained with respect to time. Finally, the energy distribution of the frequency bands for pressure and rate signals of different decomposition levels and using different wavelet types were studied with respect to time to distinguish between the rock-related and rate-related events in time. The moving reference point (MRP) technique is used to verify the results of our proposed approach. Several field cases were analyzed in this study to show the robustness of the proposed approach. The events identified using the proposed approach were in good agreement with the established techniques in the literatures such as Nolte-Smith and moving reference point (MRP). The identified events were related to physical events happening during fracture propagation, such as height growth, the opening of the natural fracture system, screen-out, and proppant entering the formation. The main advantage of the developed methodology is its ability to identify fracturing events more accurately and earlier in time than other techniques. The novelty of this research is detecting the fracturing events in time independently of the assumptions of fracture and well geometry. Ultimately, this technique helps to improve treatment designs and efficiency by analyzing fracture and formation behavior of the treatment and enhancing decision-making during execution, by providing real-time indications of fracture behavior.

Casabe is a multilayer field (20 reservoirs distributed in 3 formations) characterized high heterogeneous nature, limited sand continuity, unfavorable mobility, and high sediment production due to a poor consolidation of the reservoir. The ongoing waterflooding process has a well defined five-spot pattern where injection wells have selective strings installed, and production is commingled. Under these conditions, shut-in wells for reservoir pressure acquisition are challenging activities with high operational risks related to compromised mechanical integrity and sediment production. Likewise, the commingled production scheme affects the deconvolute pressure data process and promotes crossflow effects leading to inconsistent results. Finally, stoping the well involves production loss and disruption in waterflooding balance. The reservoir pressure is a critical requirement to run an analytic optimization methodology implemented in 2017. Casabe had proven that selective injection string offers a unique opportunity to acquire quality reservoir pressure data by reservoir unit using the Downhole Dummy Pressure Sensors (DDPS), overcoming all the above issues when acquired in producers. This paper presents how a waterflooding optimization methodology coupled with a quality reservoir pressure acquisition enhanced reservoir surveillance by triggering actions to optimize the waterflooding volumetric balance, thus, reaching a production-injection system stabilization. This enhancement changed the area production decline trend and allowed to contact more zones and produce oil from constrained layers.

The onshore Senoro field is an Indonesian carbonate pinnacle reef gas reservoir that so far has produced around 15% of the estimated original gas in place (OGIP). Twelve wells have been drilled consisting of ten production wells, one disposal well, and one monitoring well. All production wells were equipped with a permanent downhole gauge (PDG) to obtain near-bottom hole pressure data. A p/Z plot [ 1 ] of the pressure data exhibits a non-linear trend suggestive of pressure support from the aquifer or, perhaps, an adjacent gas reservoir in restricted communication with the main reservoir. If the non-linear trend is due to aquifer support, analysis assuming a weak water drive yields a bigger estimate of OGIP, and vice versa. Analysis of reservoir pressure and production data alone can result in unacceptably-high uncertainty related to drive mechanism and OGIP. This paper describes how cased-hole saturation logging from the gas reservoir across the contact and into the aquifer was integrated with other surveillance techniques based on pressure and production data to reduce the uncertainty and improve definition of drive mechanism and estimates of OGIP. Core data and pressure transient analysis in the Senoro field shows that the gas zone has a permeability in the range of 50 milidarcy (md) to 200 md, while the aquifer, which is mainly found in an underlying platform facies, has a much lower permeability in the range of 1 md to 40 md. The high permeability contrast between gas and water zone was expected to result in weak pressure support from the aquifer. Moreover, a tight streak is found in the middle of the aquifer which virtually eliminates bottom-drive aquifer support. Nevertheless, ongoing surveillance, including analysis of production data using flowing material balance and type curve analysis, indicates there is pressure support. Therefore, to address the uncertainty about aquifer support, it is necessary to evaluate the aquifer performance with other surveillance techniques to augment the PDG data. These other techniques included annual time-lapse saturation logging in the monitoring well, and static (wireline) bottomhole pressure (SBHP) surveys taken in select production wells and the monitoring well to estimate gas and aquifer pressure. After four years of production, the latest saturation log shows increased water saturation above the initial depth of the gas-water contact (GWC), indicating movement of the aquifer into the bottom of the gas column at the flank of the reservoir. The SBHP survey in the aquifer also shows that aquifer pressure has dropped by 330 psi compare to the initial pressure taken with a wireline formation tester. This compares to a pressure decrease of 370 psi in the overlying gas reservoir. Analysis of the current gas reservoir pressure trend, and the current aquifer trend, shows that the current depth of the GWC is about 50 feet shallower than the initial depth, which is consistent with the depth of the increased water saturation seen in saturation logging in the flank monitoring well. This result is consistent with the match from a simulation model with a weak water drive. Conversely, if a strong water drive is assumed, the decline in aquifer pressure will be smaller than observed and the GWC will be higher than observed. Sensitivity to combination of gas expansion energy and aquifer strength has been done to narrow the range of OGIP. The results described in this paper illustrate the benefit of integrating saturation and pressure measurements from the aquifer with other surveillance data to better measure aquifer performance, determine drive mechanism, estimate OGIP and recovery, forecast production, and anticipate problematic water production in a gas reservoir.

This paper presents a case study of fracture interaction mitigation in a multistage horizontal stimulation of an offshore Black Sea well. A multi-faceted approach in applying lessons learned and pre-job geo-mechanical analysis of depletion-induced stress differential and its effects on fracture interactions will be discussed. Details of on-the-job, real-time bottom-hole pressure monitoring of nearby wells, with the effort of on-the-fly pumping schedule changes, will also be provided. An analysis was conducted on past fracture interactions observed from multistage stimulation jobs in the area. Depletion, distances between producing wells, and a stress analysis was performed using fracture simulation software, and a consequent analysis of fracture geometry was applied. A bottom-hole gauge pressure profile assessment of nearby wells, including the pre-stimulation, shut-in, and post-stimulation period of the targeted well, was completed. A redesigned treatment was applied, considering a mitigation plan for potential on-the-fly changes during pumping. A holistic tracer analysis of production contribution between stages and wells was performed, with the goal of understanding possible crossflow of production fluids. Past-fracture interaction events have been analyzed, and clear drivers for fracture hit communication were observed. Extreme depletion effects were a primary factor in enabling fracture communication. The preferential fracture growth was further enabled owing to the continuous production of nearby wells and no shut-in implementation. The 3D geo-mechanical model was built using pertinent data from the targeted and nearby wells. The model was further optimized using fracture geometry outputs, and constraints were input to limit the fracture growth and avoid communication. The outcome of the analysis showed a clear driving force behind the interactions was depletion. An on-the-job assessment of diagnostic tests yielded a heterogeneous behavior of the horizontal segment, further proving stress differentials along the lateral. An overall chemical tracer analysis of the targeted and nearby wells was completed using pre- and post-stimulation fluid samples. The results were crucial in understanding the stimulation approach and possible crossflow effects due to fracture communication. Additionally, using bottom-hole temperature readings, a rudimentary cool-down and heat-back analysis was performed to better understand possible fluid interactions with nearby wells and optimize fluid design. Intra-stage fracture interference presents unique events and challenges that are typically managed on a case-by-case basis, and this work presents the critical analyses that are paramount to planning stimulation treatments in highly depleted segments and reservoirs with wells in close proximity.

Since 2010, hydrocarbon production from long horizontal wells targeting shales has become the norm for industry leaders. Because of the steep decline rates, it is vital to understand the reservoir and its properties before going through with a full-scale fracture stimulation. Through the application of Diagnostic Fracture Injection Tests (DFIT), one can determine accurate estimates of closure pressure, net pressure, pore pressure, formation permeability, and induced fracture geometry. The Utica shale is among the most promising reservoirs of the future, but there is limited information available discussing its properties. In SPE-196149-MS, we analyzed a DFIT from one horizontal well targeting the Utica. However, in order to fully understand the Utica shale at scale, further analysis is required. In this study, we will present three additional horizontal wells targeting the Utica, and analyze the pressure and its derivative to accurately estimate the properties mentioned above. DFIT analysis is an advanced technique to accurately predict stress regimes and reservoir properties. However, interpretation of DFIT data is challenging, especially in shale formations. In this study, we overview the geologic properties of the Utica shale, discuss the development of DFIT analysis and its governing equations, then present the three data sets and resulting conclusions. We specifically discuss the Tangent Line Method, the Compliance Method, and the Variable Compliance method in detail, while comparing their underlying equations and assumptions to determine closure pressure. After-Closure analysis is then performed in order to verify fracture closure and identify flow regimes. Through linear regression of this data, pore pressure from a linear flow regime is extrapolated, and through numerical simulation, key reservoir properties, such as permeability and fracture geometry, are estimated for the Utica shale. The DFIT interpretation and simulation results from this study are very insightful. Interpreting the GdP/dG function, the closure pressure ranges from 4,943 psi to 6,141 psi, contributing to a closure pressure gradient of 0.797 to 0.891 psi/ft for the Utica shale. Based on the pressure transient analysis, the pore pressure ranges from 3,238 psi to 4,064 psi, contributing to a pore pressure gradient of 0.486 to 0.616 psi/ft for the Utica shale. Additionally, field wide ranges of reservoirs properties are presented, allowing industry to further optimize their drilling and fracing techniques in the Utica shale. Two of the wells in this study are close in proximity and show very similar results both in After-Closure analysis and in pressure response curves. The third well displays a different GdP/dG response, leak off characteristics, pressure transient behaviors, formation permeability, and fracture geometry. This variance in results can be attributed to regional differences in geology, stresses, and pressures. Therefore, operators need to consider regional differences in reservoir properties in order to enhance the development of Utica shale and unlock all potential recoverable hydrocarbons.

This paper presents the analysis and results of the Jet Pump (JP) applications in the two oil fields: Well -A, for customer in U.A.E, and Well-B for customer in Oman. Well-A was a deviated well with 3-1/2-inch single string completion. The tubing-string was equipped with three Side Pocket Mandrels (SPM). Based on preliminary screening for Artificial Lift Systems (ALS) against the provided well data, the jet pump system was found the most suitable ALS method. Jet pump was evaluated for its efficiency in reviving a dead well with rig less installation using Jet Evaluation and Modeling Software (JEMS). Thus, a reverse circulation JP was straddled across the last SPM in the tubing using two tubing packers. The power fluid was then injected through casing which entered the JP to create the drawdown required to bring the formation fluid through tubing to the surface. The dead well was produced successfully at different injection pressures and rates for four months. The production results were compared to the theoretical model of JEMS to assess the JP performance. The Well-B was a newly side tracked well where customer intended to use a jet pump for offloading the kill fluid of well from its last zone. A 2-7/8-inch bottom hole assembly of JP was run at 9,348 ft depth during the well completion. Jet pump was freely dropped in the well to offload the kill fluid and revive the production. Rig pump was used to inject power fluid at high pressure in the tubing and returned fluids were taken from the annulus. Constant samples of produced liquid were taken to ensure the kill fluid has been offloaded and the reservoir started contributing its fluid. Jet pump was retrieved with the help of slick line once satisfactory results were received at the surface. The well was successfully offloaded at around 900 bbl. of gross fluid using JP technology.

The complex pore structure and storage mechanism of shales make the mass transport in these ultratight reservoirs complicated and significantly different from typical conventional rocks. A substantial fraction of total pore volume in organic-rich ultratight reservoirs consists of nanopores in which the notion of viscous flow may become irrelevant. Instead, multiple transport and storage mechanisms should be considered to model fluid transport within the shale matrix, including molecular diffusion, Knudsen diffusion, surface diffusion, and sorption. This paper presents a diffusion-based semi-analytical model for a single-component gas transport within an infinite-acting organic-rich ultratight matrix. The model treats free and sorbed gas as two phases coexisting in nanopores. The overall mass conservation equation for both phases is transformed into one governing equation solely based on the concentration (density) of the free-phase. As a result, the partial differential equation (PDE) governing the overall mass transport carries two newly-defined nonlinear terms; namely, overall diffusivity, D , and sorption-corrected porosity, Φ. The D term accounts for the molecular, Knudsen, and surface diffusivity, and the Φ term considers the mass exchange between free- and sorbed-phases under sorption equilibrium condition. Both D and Φ are functions of free-phase concentration. The nonlinear PDE is solved by applying a piecewise-constant-coefficient technique that divides the domain under consideration into an arbitrary number of subdomains. Each subdomain is assigned with a constant D and Φ. The diffusion-based model is validated against numerical simulation. The model is then used to investigate the impact of surface diffusivity, Knudsen diffusivity, porosity, and adsorption capacity on gas transport within the ultratight formation. Further, the model is utilized to study gas transport and production from Barnett, Marcellus, and New Albany shales. The results show that surface diffusion significantly contributes to gas production in shales with high surface diffusivity and adsorption capacity and when the Knudsen diffusivity and total porosity are small. Thus, neglecting surface diffusion in organic-rich shales may result in the underestimation of gas production.

The transient volume of investigation extends the concepts of radius and depth of investigation (for radial and linear flow, respectively). However, it is far more general, with much broader applicability. Unlike the specific cases of radius and depth of investigation, the volume of investigation is independent of flow regime, geometry, and model. Thus, the transient volume of investigation is applicable even when no recognizable flow regime is present. The transient volume of investigation is based on fundamental properties common to all constant-terminal-rate solutions to the diffusivity equation. It is defined as the minimum reservoir volume necessary to provide sufficient pressure support to produce the observed rate of change of sand-face pressure as a function of time. The volume of investigation is a paradigm-changing concept. It is the only meaningful reservoir characteristic that is both easily estimated and model independent. It provides a rigorous lower bound on fluid in place investigated as a function of time during a test, independent of flow regime, geometry, model, and even permeability heterogeneity or anisotropy.