Download or read book Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs written by James Cody Statton and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Production forecasting in shale (ultra-low permeability) gas reservoirs is of great interest due to the advent of multi-stage fracturing and horizontal drilling. The well renowned production forecasting model, Arps' Hyperbolic Decline Model, is widely used in industry to forecast shale gas wells. Left unconstrained, the model often overestimates reserves by a great deal. A minimum decline rate is imposed to prevent overestimation of reserves but with less than ten years of production history available to analyze, an accurate minimum decline rate is currently unknown; an educated guess of 5% minimum decline is often imposed. Other decline curve models have been proposed with the theoretical advantage of being able to match linear flow followed by a transition to boundary dominated flow. This thesis investigates the applicability of the Stretched Exponential Production Decline Model (SEPD) and compares it to the industry standard, Arps' with a minimum decline rate. When possible, we investigate an SEPD type curve. Simulated data is analyzed to show advantages of the SEPD model and provide a comparison to Arps' model with an imposed minimum decline rate of 5% where the full production history is known. Long-term production behavior is provided by an analytical solution for a homogenous reservoir with homogenous hydraulic fractures. Various simulations from short-term linear flow (~1 year) to long-term linear flow (~20 years) show the ability of the models to handle onset of boundary dominated flow at various times during production history. SEPD provides more accurate reserves estimates when linear flow ends at 5 years or earlier. Both models provide sufficient reserves estimates for longer-term linear flow scenarios. Barnett Shale production data demonstrates the ability of the models to forecast field data. Denton and Tarrant County wells are analyzed as groups and individually. SEPD type curves generated with 2004 well groups provide forecasts for wells drilled in subsequent years. This study suggests a type curve is most useful when 24 months or less is available to forecast. The SEPD model generally provides more conservative forecasts and EUR estimates than Arps' model with a minimum decline rate of 5%.

Download or read book Evaluation of the Stretched Exponential Production Decline Model and Comparison to Other Decline Models for Shale Reservoirs written by Dong Li and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The discovery and development of shale oil/gas has changed the energy industry. By 2040, shale gas production will account for 50% of the total natural gas production of the U.S. Due to the extremely low permeability of shale reservoirs, shale gas wells exhibit much longer transient flow periods than conventional wells, and this makes it inappropriate to use conventional methods of evaluating estimated ultimate recovery (EUR) of wells in these reservoirs. Therefore, new methods of forecasting shale wells are needed. In this study, I focused on the stretched exponential production decline model (SEPD), and particularly Yu’s modification of the model (YM-SEPD). I compared the results with other methods, including Duong’s method, and the Arps hyperbolic model. SEPD provided the most reliable EURs for shale gas well when excluding early off-trend data. YM-SEPD gave results comparable to SEPD and is much easier to apply. It is therefore the method we recommend for shale wells.

Download or read book Stretched Exponential Decline Model as a Probabilistic and Deterministic Tool for Production Forecasting and Reserve Estimation in Oil and Gas Shales written by Babak Akbarnejad Nesheli and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Today everyone seems to agree that ultra-low permeability and shale reservoirs have become the potentials to transform North America's oil and gas industry to a new phase. Unfortunately, transient flow is of long duration (perhaps life of the well) in ultra-low permeability reservoirs, and traditional decline curve analysis (DCA) models can lead to significantly over-optimistic production forecasts without additional safeguards. Stretched Exponential decline model (SEDM) gives considerably more stabilized production forecast than traditional DCA models and in this work it is shown that it produces unchanging EUR forecasts after only two-three years of production data are available in selected reservoirs, notably the Barnett Shale. For an individual well, the SEDM model parameters, can be determined by the method of least squares in various ways, but the inherent nonlinear character of the least squares problem cannot be bypassed. To assure a unique solution to the parameter estimation problem, this work suggests a physics-based regularization approach, based on critical velocity concept. Applied to selected Barnett Shale gas wells, the suggested method leads to reliable and consistent EURs. To further understand the interaction of the different fracture properties on reservoir response and production decline curve behavior, a series of Discrete Fracture Network (DFN) simulations were performed. Results show that at least a 3-layer model is required to reproduce the decline behavior as captured in the published SEDM parameters for Barnett Shale. Further, DFN modeling implies a large number of parameters like fracture density and fracture length are in such a way that their effect can be compensated by the other one. The results of DFN modeling of several Barnett Shale horizontal wells, with numerous fracture stages, showed a very good agreement with the estimated SEDM model for the same wells. Estimation of P90 reserves that meet SEC criteria is required by law for all companies that raise capital in the United States. Estimation of P50 and P10 reserves that meet SPE/WPC/AAPG/SPEE Petroleum Resources Management System (PRMS) criteria is important for internal resource inventories for most companies. In this work a systematic methodology was developed to quantify the range of uncertainty in production forecast using SEDM. This methodology can be used as a probabilistic tool to quantify P90, P50, and P10 reserves and hence might provide one possible way to satisfy the various legal and technical-society-suggested criteria.

Download or read book Application of Probabilistic Decline Curve Analysis to Unconventional Reservoirs written by Uchenna C. Egbe and published by . This book was released on 2022 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents the various probabilistic methodology for forecasting petroleum production in shale reservoirs. Two statistical methods are investigated, Bayesian and frequentist, combined with various decline curve deterministic models. A robust analysis of well-completion properties and how they affect the production forecast is carried out. Lastly, a look into the uncertainties introduced by the statistical methods and the decline curve models are investigated to discover any correlation and plays that otherwise would not be apparent. We investigated two Bayesian methods - Absolute Bayesian Computation (ABC) and GIBBS sampler - and two frequentist methods - Conventional Bootstrap (BS) and Modified Bootstrap (MBS). We combined these statistical methods with five empirical models - Arps, Duong, Power Law Model (PLE), Logistic Growth Model (LGA), and Stretched Exponential Decline Model (SEPD) - and an analytical Jacobi 2 theta model. This allowed us to make a robust comparison of all these approaches on various unconventional plays across the United States, including Permian, Marcellus, Eagle Ford, Haynesville, Barnett, and Bakken shale, to get detailed insight on how to forecast production with minimal prediction errors effectively. Analysis was carried out on a total of 1800 wells with varying production history data lengths ranging from 12 to 60 months on a 12-month increment and a total production length of 96 months. We developed a novel approach for developing and integrating informative model parameter priors into the Bayesian statistical methods. Previous work assumed a uniform distribution for model parameter priors, which was inaccurate and negatively impacted forecasting performance. Our results show the significant superior performance of the Bayesian methods, most notably at early hindcast size (12 to 24 months production history). Furthermore, we discovered that production history length was the most critical factor in production forecasting that leveled the performance of all probabilistic methods regardless of the decline curve model or statistical methodology implemented. The novelty of this work relies on the development of informative priors for the Bayesian methodologies and the robust combination of statistical methods and model combination studied on a wide variety of shale plays. In addition, the whole methodology was automated in a programming language and can be easily reproduced and used to make production forecasts accurately.

Download or read book A Study of Decline Curve Analysis in the Elm Coulee Field written by Seth C Harris and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last two years, due in part to the collapse of natural gas prices, the oil industry has turned its focus from shale gas exploration to shale oil/tight oil. Some of the important plays under development include the Bakken, Eagle Ford, and Niobrara. New decline curve methods have been developed to replace the standard Arps model for use in shale gas wells, but much less study has been done to verify the accuracy of these methods in shale oil wells. The examples that I investigated were Arps with a 5% minimum decline rate as well as the stretched exponential model (SEPD) and the Duong method. There is a great amount of uncertainty about how to calculate reserves in shale reservoirs with long multi-fractured horizontals, since these wells have not yet been produced to abandonment. Although the Arps model can reliably describe conventional reservoir production decline, it is still uncertain which empirical decline curve method best describes a shale oil well to get a rapid assessment of expected recovery. My focus began in the oil window of the Eagle Ford, but I ultimately chose to study the Elm Coulee field (Bakken formation) instead to see what lessons an older tight oil play could lend to newer plays such as the Eagle Ford. Contrary to existing literature, I have found evidence from diagnostic plots that many horizontal wells in the Elm Coulee that began producing in 2006 and 2007 have entered boundary-dominated flow. In order to accommodate boundary flow I have modified the Duong and SEPD methods such that once boundary-dominated flow begins the decline is described by an Arps curve with a b-value of 0.3. What I found from hindcasting was that early production history, up to six months, is generally detrimental to accurate forecasting in the Elm Coulee. This was particularly true for the Arps with 5% minimum decline or the Duong method. Early production history often contains apparent bilinear flow or no discernible trend. There are many possible reasons for this, particularly the rapid decrease in bottomhole pressure and production of fracture fluid. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151644

Download or read book Applying Decline Curve Analysis in the Liquid rich Shales written by Purvi Indras and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: With the emergence of liquid rich shale (LRS) plays like Eagle Ford and Northern Barnett, the petroleum industry needs a simple, easily applied technique that provides reliable estimates of future production rates in this kind of reservoir. There is no guarantee that methodology that has proved to work in gas reservoirs will necessarily be appropriate in LRS reservoirs. In this work, we found that without corrections of early data, the Stretched Exponential Production Decline (SEPD) model, designed for transient flow, usually produces pessimistic forecasts of future production. The Duong method, another transient model, may be reasonable during long term transient linear flow, but notably optimistic after boundary-dominated flow (BDF) appears. For wells in BDF, the Arps model provides reasonable forecasts, but the Arps model may not be accurate when applied to transient data. A hybrid of early transient and later BDF models proves to be a reasonable solution to the forecasting problem in LRS. In addition, use of diagnostic plots (like log-log rate-time and log-log rate-material balance time plots) improves confidence in flow regime identification and production forecasting. In some LRS's, BDF is observed within 12 months. In any case, it is essential to identify or to estimate the time to reach BDF and to discontinue use of transient flow models after BDF appears or is expected. We validated our methodology using "hindcast analysis"; that is, matching the first half of production history to determine model parameters, then forecasting the second half of history and comparing to observed production data. We also found that application of pressure-corrected rates in decline curve analysis (DCA) may substantially improve the interpretation of data from unconventional oil wells flowing under unstable operating conditions. Fetkovich (hydraulically fractured well) type curve analysis can be added to improve confidence in flow regime identification from diagnostic plots and to estimate the Arps hyperbolic exponent b from the matching b stem on the type curve, which can then be extrapolated to determine estimated ultimate recovery. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/152507

Download or read book Study of the Effect of Fracture Completion Variables on Decline Curve Parameters for Long term Production Forecast of Shale Liquids written by Eshwar C. Yennigalla and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Shale reservoir exploitation using multiple stage hydraulically fractured horizontal wells has proved the existence of considerable amount of oil and gas reserves throughout the world. Forecasts of future production from these reservoirs based on the fracture stimulation parameters and reservoir properties has led to a better understanding of the duration of important flow regimes and parameters used in production forecasting models. The decline curve analysis considered in the study is a combination of the traditional Arps and Stretched Exponential production decline models designed to fit the forecasts for individual flow regime production data. Simulations using identical reservoir properties but different fracture completion parameters were analyzed and fit to decline models. The parameters considered in our study are fracture half-length, fracture spacing, stimulated reservoir volume permeability and matrix permeability.

Download or read book Comparison of Emperical Decline Curve Analysis for Shale Wells written by Mohammed Sami A. Kanfar and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This study compares four recently developed decline curve methods and the traditional Arps or Fetkovich approach. The four methods which are empirically formulated for shale and tight gas wells are: 1. Power Law Exponential Decline (PLE). 2. Stretched Exponential Decline (SEPD). 3. Duong Method. 4. Logistic Growth Model (LGM). Each method has different tuning parameters and equation forms. The main objective of this work is to determine the best method(s) in terms of Estimated Ultimate Recovery (EUR) accuracy, goodness of fit, and ease of matching. In addition, these methods are compared against each other at different production times in order to understand the effect of production time on forecasts. As a part of validation process, all methods are benchmarked against simulation. This study compares the decline methods to four simulation cases which represent the common shale declines observed in the field. Shale wells, which are completed with horizontal wells and multiple traverse highly-conductive hydraulic fractures, exhibit long transient linear flow. Based on certain models, linear flow is preceded by bilinear flow if natural fractures are present. In addition to this, linear flow is succeeded by Boundary Dominated Flow (BDF) decline when pressure wave reaches boundary. This means four declines are possible, hence four simulation cases are required for comparison. To facilitate automatic data fitting, a non-linear regression program was developed using excel VBA. The program optimizes the Least-Square (LS) objective function to find the best fit. The used optimization algorithm is the Levenberg-Marquardt Algorithm (LMA) and it is used because of its robustness and ease of use. This work shows that all methods forecast different EURs and some fit certain simulation cases better than others. In addition, no method can forecast EUR accurately without reaching BDF. Using this work, engineers can choose the best method to forecast EUR after identifying the simulation case that is most analogous to their field wells. The VBA program and the matching procedure presented here can help engineers automate these methods into their forecasting sheets. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151124

Download or read book Challenges in Modelling and Simulation of Shale Gas Reservoirs written by Jebraeel Gholinezhad and published by Springer. This book was released on 2017-12-27 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the problems involved in the modelling and simulation of shale gas reservoirs, and details recent advances in the field. It discusses various modelling and simulation challenges, such as the complexity of fracture networks, adsorption phenomena, non-Darcy flow, and natural fracture networks, presenting the latest findings in these areas. It also discusses the difficulties of developing shale gas models, and compares analytical modelling and numerical simulations of shale gas reservoirs with those of conventional reservoirs. Offering a comprehensive review of the state-of-the-art in developing shale gas models and simulators in the upstream oil industry, it allows readers to gain a better understanding of these reservoirs and encourages more systematic research on efficient exploitation of shale gas plays. It is a valuable resource for researchers interested in the modelling of unconventional reservoirs and graduate students studying reservoir engineering. It is also of interest to practising reservoir and production engineers.

Download or read book History matching and Forecasting of Three Unconventional Oil and Gas Reservoirs Using Decline Analyses and Type Curves written by Hammad Ahmed and published by . This book was released on 2019 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reservoir modeling of shale gas and tight oil presents numerous challenges due to complicated transport mechanisms and the existence of fracture networks. Even then, oil and gas companies have not slowed down on shale hydrocarbon investment and production using horizontal well drilling and hydraulic fracturing techniques. Many small oil companies may not have the budget to build a reservoir model which typically requires drilling test wells and performing well logging measurements. Even for large oil companies, building a reservoir model is not worthwhile for the evaluation of small-scale oil fields. Comprehensive numerical simulation methods are likely impractical in those cases. Decline Curve Analysis (DCA) is one of the most convenient and practical techniques in order to forecast the production of these reservoirs. With the rapid increase in shale hydrocarbon production over the past 30 years, there have been numerous production data for shale gas reservoirs. Many different DCA models have been constructed to model the shale hydrocarbon production rate, from the classical Arps to the latest and more advanced models; each has its advantages and shortcomings. In practice and in all existing commercial DCA software, most of these DCA models are implemented and open to be used. Most of the deterministic DCA models are empirical and lack a physical background so that they cannot be used for history-matching of the reservoir properties. In this study, popular DCA models for shale gas reservoirs are reviewed, including the types of reservoirs they fit. Their advantages and disadvantages have also been presented. This work will serve as a guideline for petroleum engineers to determine which DCA models should be applied to different shale hydrocarbon fields and production periods. The research objective also includes evaluating the performance of top unconventional plays (Bakken, Barnett, and Eagle Ford). Productions by counties are analyzed and compared to see how they stack up against each other. One section of this study also sheds some light on the future of shale gas and tight oil plays based on the simulation of models created.

Download or read book Production Analysis and Forecasting of Shale Reservoirs Using Simple Mechanistic and Statistical Modeling written by Leopoldo Matias Ruiz Maraggi and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate production analysis and forecasting of well’s performance is essential to estimate reserves and to develop strategies to optimize hydrocarbon recovery. In the case of shale resources, this task is particularly challenging for the following reasons. First, these reservoirs show long periods of transient linear flow in which the reservoir volume grows continuously over time acting without bounds. Second, variable operating conditions cause scatter and abrupt production changes. Finally, the presence of competing flow mechanisms, heterogeneities, and multi-phase flow effects make the production analysis more complex. Detailed numerical flow models can address the complexities present in unconventional reservoirs. However, these models suffer from the following limitations: (a) the uncertainty of many input parameters, (b) susceptibility to overfit the data, (c) lack of interpretability of their results, and (d) high computational expense. This dissertation provides new and simple mechanistic and statistical modeling tools suitable to improve the production analysis and forecasts of shale reservoirs. This work presents solutions to the following research problems. This study develops and applies a new two-phase (oil and gas) flow suitable to history-match and forecast production of tight-oil and gas-condensate reservoirs producing below bubble- and dew-point conditions, respectively. It solves flow equations in dimensionless form and uses only two scaling parameters (hydrocarbon in-place and characteristic time) to history-match production. For this reason, the model requires minimal time to run making it ideal for decline curve analysis on large numbers of wells. This research illustrates the development and application of a Bayesian framework that generates probabilistic production history matches and forecasts to address the uncertainty of model’s estimates. This work uses an adaptative Metropolis-Hastings Markov chain Monte Carlo (MCMC) algorithm to guarantee a fast convergence of the Markov chains by accounting for the correlation among model’s parameters. In addition, this study calibrates the model’s probabilistic estimates using hindcasting and evaluates the inferences robustness using posterior predictive checks. This dissertation examines the problem of evaluation, ranking and selection, and averaging of models for improved probabilistic production history-matching and forecasting. We illustrate the assessment of the predictive accuracy of four rate-time models using the expected log predictive density (elpd) accuracy metric along with cross-validation techniques (leave-one-out and leave-future-out). The elpd metric provides a measure of out-of-sample predictive accuracy of a model’s posterior distribution. The application of Pareto smoothed importance sampling (PSIS) allows to use cross-validation techniques without the need of refitting Bayesian models. Using the Bayesian Bootstrap, this work generates a model ensemble that weighs each individual model based on the accuracy of its predictions. Finally, this research applies a novel deconvolution technique to incorporate changing operating conditions into rate-time analysis of tight-oil and shale gas reservoirs. Furthermore, this work quantifies the errors and discusses the limitations of the standard rate-transient analysis technique used in production analysis of unconventional reservoirs: rate normalization and material balance time

Download or read book Development of New Decline Model for Shale Oil Reserves written by Samit Shah and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis provides a new methodology to forecast ultimate recovery, based on more reliable production forecast for shale oil wells using historical production data. Compared to available decline curve methods including Arps (AIME: 160, 228-247), Valko (SPE 134231) and Duong (SPE 137748), this method is more accurate and more conservative. Production forecasts play a vital role in determining the value of oil or gas wells, and improved accuracy enhances management decisions on field development. The new, more accurate method was verified using both field data and numerical simulations. This method can potentially be used in most shale reservoirs producing single-phase liquid.

Download or read book Comparison of Various Deterministic Forecasting Techniques in Shale Gas Reservoirs with Emphasis on the Duong Method written by Krunal Jaykant Joshi and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a huge demand in the industry to forecast production in shale gas reservoirs accurately. There are many methods including volumetric, Decline Curve Analysis (DCA), analytical simulation and numerical simulation. Each one of these methods has its advantages and disadvantages, but only the DCA technique can use readily available production data to forecast rapidly and to an extent accurately. The DCA methods in use in the industry such as the Arps method had originally been developed for Boundary dominated flow (BDF) wells but it has been observed in shale reservoirs the predominant flow regime is transient flow. Therefore it was imperative to develop newer models to match and forecast transient flow regimes. The SEDM/SEPD, the Duong model and the Arps with a minimum decline rate are models that have the ability to match and forecast wells with transient flow followed by boundary flow. I have revised the Duong model to forecast better than the original model. I have also observed a certain variation of the Duong model proves to be a robust model for most of the well cases and flow regimes. The modified Duong has been shown to work best compared to other deterministic models in most cases. For grouped datasets the SPED & Duong models forecast accurately while the Modified Arps does a poor job.

Download or read book Production Optimization and Forecasting of Shale Gas Wells Using Simulation Models and Decline Curve Analysis written by Peter O. Ikewun and published by . This book was released on 2012 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Production data from the Eagle Ford shale (an analogue to the Shublik shale of Alaska) was compiled from three neighboring counties and analyzed using decline curve analysis (DCA) to correlate production performance with completion method (horizontal leg/stages of fracture) and length of horizontal leg. Generic simulation models were built and run using a realistic range of properties. Simulation results provided a better understanding of interplay between static properties and dynamic behavior. Results from the DCA of 24 producing wells with production histories of 9-57 months showed, for most cases, an increase in reserves with more fracture stages. However, the DCA generated different forecasts depending on which part of the data were used. This clearly indicated the need for running simulations. Simulation runs can generate more reliable production forecast of which the decline part can be used to evaluate the capability of DCA to reproduce the production profiles. A combination of simulation models and DCA was used to optimize production and forecasting. Simulation models were used to optimize production for a range of different reservoir and completion parameters. The ability for DCA to reproduce simulated results (built with similar data from the Eagle Ford) for wells with different production periods was also analyzed. This results in better and more reliable production forecasts for the Eagle Ford and other young producing shale reservoirs possessing short production history. Modeling of the complex reservoir geometry and fracture networks of these types of reservoirs would give an extensive understanding of the flow mechanics.

Download or read book Shale Analytics written by Shahab D. Mohaghegh and published by Springer. This book was released on 2017-02-09 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the application of modern information technology to reservoir modeling and well management in shale. While covering Shale Analytics, it focuses on reservoir modeling and production management of shale plays, since conventional reservoir and production modeling techniques do not perform well in this environment. Topics covered include tools for analysis, predictive modeling and optimization of production from shale in the presence of massive multi-cluster, multi-stage hydraulic fractures. Given the fact that the physics of storage and fluid flow in shale are not well-understood and well-defined, Shale Analytics avoids making simplifying assumptions and concentrates on facts (Hard Data - Field Measurements) to reach conclusions. Also discussed are important insights into understanding completion practices and re-frac candidate selection and design. The flexibility and power of the technique is demonstrated in numerous real-world situations.

Download or read book COMBINING DECLINE CURVE ANALYSIS AND GEOSTATISTICS TO FORECAST GAS PRODUCTION IN THE MARCELLUS SHALE written by Zhenke Xi and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditionally, in order to estimate the production potential at a new, prospective field site via simulation or material balance, one needs to collect various forms of expensive field data and/or make assumptions about the nature of the formation at that site. Decline curve analysis would not be applicable in this scenario, as producing wells need to pre-exist in the target field. The objective of our work is to make first-order forecasts of production rates at prospective, undrilled sites using only production data from existing wells in the entire play. This is accomplished through co-kriging of decline curve parameter values, where the parameter values are obtained at each existing well by fitting an appropriate decline model to the production history. Co-kriging gives the best linear unbiased prediction of parameter values at undrilled locations, and also estimates uncertainty in those predictions. Thus, we can obtain production forecasts at P10, P50, and P90, as well as calculate EUR at those same levels, across the spatial domain of the play.To demonstrate the proposed methodology, we use monthly gas flow rates and well locations from the Marcellus shale gas play in this research. Looking only at horizontal and directional wells, the gas production rates at each well are carefully filtered and screened. Also, we normalize the rates by perforation interval length. We keep only production histories of 24 months or longer in duration to ensure good decline curve fits. Ultimately, we are left with 5,637 production records. Here, we choose Duongs decline model to represent production decline in this shale gas play, and fitting of this decline curve is accomplished through ordinary least square regression.Interpolation is done by universal co-kriging with consideration to correlation between the four parameters in Duongs model, which also show linear trends (the parameters show dependency on the x and y spatial coordinates). Kriging gives us the optimal decline curve coefficients at new locations (P50 curve), as well as the variance in these coefficient estimates (used to establish P10 and P90 curves). We are also able to map EUR for 25 years across the study area. Finally, the universal co-kriging model is cross-validated with a leave-one-out scheme, which shows significant but not unreasonable error in decline curve coefficient prediction. The methods proposed are easy to implement and do not require various expensive data like permeability, bottom hole pressure, etc., giving operators a risk-based analysis of prospective sites. While we demonstrate the procedure on the Marcellus shale gas play, it is applicable to any play with existing producing wells. We also make this analysis available to the public in a user-friendly web app.

Download or read book Integrative Understanding of Shale Gas Reservoirs written by Kun Sang Lee and published by Springer. This book was released on 2016-02-03 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely book begins with an overview of shale gas reservoir features such as natural fracture systems, multi-fractured horizontal wells, adsorption/desorption of methane, and non-linear flow within the reservoir. Geomechanical modelling, an aspect of importance in ultra-low permeability reservoirs, is also presented in detail. Taking these complex features of shale reservoirs into account, the authors develop a numerical model, which is verified with field data using the history matching technique. Based on this model, the pressure transient and production characteristics of a fractured horizontal well in a shale gas reservoir are analysed with respect to reservoir and fracture properties. Methods for the estimation of shale properties are also detailed. Minifrac tests, rate transient tests (RTA), and type curve matching are used to estimate the initial pressure, permeability, and fracture half-length. Lastly, future technologies such as the technique of injecting CO2 into shale reservoirs are presented. The book will be of interest to industrial practitioners, as well as to academics and graduate students in the field of reservoir engineering.