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Applying Decline Curve Analysis In The Liquid Rich Shales
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Book Synopsis Applying Decline Curve Analysis in the Liquid-rich Shales by : Purvi Indras
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
Book Synopsis Application of Decline-curve Analysis in Oil Reservoirs Using a Universal Fitting Equation by : Abdelhafidh Fekkane
Download or read book Application of Decline-curve Analysis in Oil Reservoirs Using a Universal Fitting Equation written by Abdelhafidh Fekkane and published by . This book was released on 2001 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Application of Probabilistic Decline Curve Analysis to Unconventional Reservoirs by : Uchenna C. Egbe
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.
Book Synopsis Decline Curve Analysis and Enhanced Shale Oil Recovery Based on Eagle Ford Shale Data by : Dieudonne K. Delaihdem
Download or read book Decline Curve Analysis and Enhanced Shale Oil Recovery Based on Eagle Ford Shale Data written by Dieudonne K. Delaihdem and published by . This book was released on 2014 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transient and fracture dominated flow regimes in tight permeability shale reservoirs with hydraulically fractured horizontal wells impose many unconventional challenges. These include execution of appropriate shale decline curve analysis and the optimization of hydrocarbons recovery. Additionally, short production profiles available are inadequate for accurate production decline analysis. This research assessed the effectiveness of Arps' decline curve analysis and recently established methods--power law exponential analysis, logistic growth analysis, Duong's method and the author's approach--to predict future production of horizontal wells in the Eagle Ford Shale. Simulation models investigated history matching, enhanced shale oil recovery, and drainage area beyond stimulated reservoir volume. Traditional Arps' hyperbolic method sufficiently analyzed past production rates, but inaccurately forecasted cumulative productions. The recent decline models show slight variations in their past performance evaluations and forecasting future production trends. The technique proposed and used in this work enhanced the successful application of Arps' hyperbolic decline from 32.5% to 80%. Simulation results indicate 4.0% primary oil recovery factor and 5.8% enhanced shale oil recovery factor using CO2 miscible injection. Based on pressure observed outside of the stimulated reservoir volume, limited to the range of data used in this study, drainage area outside stimulated reservoir volume is not significant.
Book Synopsis A Study of Decline Curve Analysis in the Elm Coulee Field by : Seth C Harris
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
Book Synopsis Analysis of Shale Production Performance Using Decline Curve Methods by : Brad Thomas Nelson
Download or read book Analysis of Shale Production Performance Using Decline Curve Methods written by Brad Thomas Nelson and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Using Decline Curve Analysis, Volumetric Analysis, and Bayesian Methodology to Quantify Uncertainty in Shale Gas Reserve Estimates by : Raul Alberto Gonzalez Jimenez
Download or read book Using Decline Curve Analysis, Volumetric Analysis, and Bayesian Methodology to Quantify Uncertainty in Shale Gas Reserve Estimates written by Raul Alberto Gonzalez Jimenez and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic decline curve analysis (PDCA) methods have been developed to quantify uncertainty in production forecasts and reserves estimates. However, the application of PDCA in shale gas reservoirs is relatively new. Limited work has been done on the performance of PDCA methods when the available production data are limited. In addition, PDCA methods have often been coupled with Arp's equations, which might not be the optimum decline curve analysis model (DCA) to use, as new DCA models for shale reservoirs have been developed. Also, decline curve methods are based on production data only and do not by themselves incorporate other types of information, such as volumetric data. My research objective was to integrate volumetric information with PDCA methods and DCA models to reliably quantify the uncertainty in production forecasts from hydraulically fractured horizontal shale gas wells, regardless of the stage of depletion. In this work, hindcasts of multiple DCA models coupled to different probabilistic methods were performed to determine the reliability of the probabilistic DCA methods. In a hindcast, only a portion of the historical data is matched; predictions are made for the remainder of the historical period and compared to the actual historical production. Most of the DCA models were well calibrated visually when used with an appropriate probabilistic method, regardless of the amount of production data available to match. Volumetric assessments, used as prior information, were incorporated to further enhance the calibration of production forecasts and reserves estimates when using the Markov Chain Monte Carlo (MCMC) as the PDCA method and the logistic growth DCA model. The proposed combination of the MCMC PDCA method, the logistic growth DCA model, and use of volumetric data provides an integrated procedure to reliably quantify the uncertainty in production forecasts and reserves estimates in shale gas reservoirs. Reliable quantification of uncertainty should yield more reliable expected values of reserves estimates, as well as more reliable assessment of upside and downside potential. This can be particularly valuable early in the development of a play, because decisions regarding continued development are based to a large degree on production forecasts and reserves estimates for early wells in the play. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/148436
Book Synopsis Comparison of Emperical Decline Curve Analysis for Shale Wells by : Mohammed Sami A. Kanfar
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
Book Synopsis Improved Reservoir Models and Production Forecasting Techniques for Multi-Stage Fractured Hydrocarbon Wells by : Ruud Weijermars
Download or read book Improved Reservoir Models and Production Forecasting Techniques for Multi-Stage Fractured Hydrocarbon Wells written by Ruud Weijermars and published by MDPI. This book was released on 2019-12-12 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: The massive increase in energy demand and the related rapid development of unconventional reservoirs has opened up exciting new energy supply opportunities along with new, seemingly intractable engineering and research challenges. The energy industry has primarily depended on a heuristic approach—rather than a systematic approach—to optimize and tackle the various challenges when developing new and improving the performance of existing unconventional reservoirs. Industry needs accurate estimations of well production performance and of the cumulative estimated ultimate reserves, accounting for uncertainty. This Special Issue presents 10 original and high-quality research articles related to the modeling of unconventional reservoirs, which showcase advanced methods for fractured reservoir simulation, and improved production forecasting techniques.
Book Synopsis Fundamentals of Gas Shale Reservoirs by : Reza Rezaee
Download or read book Fundamentals of Gas Shale Reservoirs written by Reza Rezaee and published by John Wiley & Sons. This book was released on 2015-07-01 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides comprehensive information about the key exploration, development and optimization concepts required for gas shale reservoirs Includes statistics about gas shale resources and countries that have shale gas potential Addresses the challenges that oil and gas industries may confront for gas shale reservoir exploration and development Introduces petrophysical analysis, rock physics, geomechanics and passive seismic methods for gas shale plays Details shale gas environmental issues and challenges, economic consideration for gas shale reservoirs Includes case studies of major producing gas shale formations
Book Synopsis Two Phase Linear Flow Analysis for Liquids-rich Shales by :
Download or read book Two Phase Linear Flow Analysis for Liquids-rich Shales written by and published by . This book was released on 2015 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Stretched Exponential Decline Model as a Probabilistic and Deterministic Tool for Production Forecasting and Reserve Estimation in Oil and Gas Shales by : Babak Akbarnejad Nesheli
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.
Book Synopsis Study of the Effect of Fracture Completion Variables on Decline Curve Parameters for Long-term Production Forecast of Shale Liquids by : Eshwar C. Yennigalla
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.
Book Synopsis A Production Characterization of the Eagle Ford Shale, Texas by : Nefeli George Moridis
Download or read book A Production Characterization of the Eagle Ford Shale, Texas written by Nefeli George Moridis and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We begin this research by asking "can we better estimate reserves in unconventional reservoirs using Bayes' theorem?" To attempt to answer this question, we obtained data for 68 wells in the Greater Core of the Eagle Ford Shale, Texas. As process, we eliminated the wells that did not have enough data, that did not show a production decline and/or wells that had too much data noise (this left us with 8 wells for analysis). We next performed decline curve analysis (DCA) using the Modified Hyperbolic (MH) and Power-Law Exponential (PLE) models (the two most common DCA models), consisting in user-guided analysis software. Then, the Bayesian paradigm was implemented to calibrate the same two models on the same set of wells. The primary focus of the research was the implementation of the Bayesian paradigm on the 8 well data set. We first performed a "best fit" parameter estimation using least squares optimization, which provided an optimized set of parameters for the two decline curve models. This was followed by using the Markov Chain Monte Carlo (MCMC) integration of the Bayesian posterior function for each model, which provided a full probabilistic description of its parameters. This allowed for the simulation of a number of likely realizations of the decline curves, from which first order statistics were computed to provide a confidence metric on the calibration of each model as applied to the production data of each well. Results showed variation on the calibration of the MH and PLE models. The forward models (MH and PLE) either over- or underestimate the reserves compared with the Bayesian calibrations, proving that the Bayesian paradigm was able to capture a more accurate trend of the data and thus able to determine more accurate estimates of reserves. In industry, the same decline curve models are used for unconventional wells as for conventional wells, even though we know that the same models may not apply. Based on the proposed results, we believe that Bayesian inference yields more accurate estimates of reserves for unconventional reservoirs than deterministic DCA methods. Moreover, it provides a measure of confidence on the prediction of production as as function of varying data and varying decline curve models. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155011
Book Synopsis Decline Curve Analysis in Unconventional Resource Plays Using Logistic Growth Models by : Aaron James Clark
Download or read book Decline Curve Analysis in Unconventional Resource Plays Using Logistic Growth Models written by Aaron James Clark and published by . This book was released on 2011 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current models used to forecast production in unconventional oil and gas formations are often not producing valid results. When traditional decline curve analysis models are used in shale formations, Arps b-values greater than 1 are commonly obtained, and these values yield infinite cumulative production, which is non-physical. Additional methods have been developed to prevent the unrealistic values produced, like truncating hyperbolic declines with exponential declines when a minimum production rate is reached. Truncating a hyperbolic decline with an exponential decline solves some of the problems associated with decline curve analysis, but it is not an ideal solution. The exponential decline rate used is arbitrary, and the value picked greatly effects the results of the forecast. A new empirical model has been developed and used as an alternative to traditional decline curve analysis with the Arps equation. The new model is based on the concept of logistic growth models. Logistic growth models were originally developed in the 1830s by Belgian mathematician, Pierre Verhulst, to model population growth. The new logistic model for production forecasting in ultra-tight reservoirs uses the concept of a carrying capacity. The carrying capacity provides the maximum recoverable oil or gas from a single well, and it causes all forecasts produced with this model to be within a reasonable range of known volumetrically available oil. Additionally the carrying capacity causes the production rate forecast to eventually terminate as the cumulative production approaches the carrying capacity. The new model provides a more realistic method for forecasting reserves in unconventional formations than the traditional Arps model. The typical problems encountered when using conventional decline curve analysis are not present when using the logistic model. Predictions of the future are always difficult and often subject to factors such as operating conditions, which can never be predicted. The logistic growth model is well established, robust, and flexible. It provides a method to forecast reserves, which has been shown to accurately trend to existing production data and provide a realistic forecast based on known hydrocarbon volumes.
Book Synopsis Production Analysis and Forecasting of Shale Reservoirs Using Simple Mechanistic and Statistical Modeling by : Leopoldo Matias Ruiz Maraggi
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
Book Synopsis Production Optimization and Forecasting of Shale Gas Wells Using Simulation Models and Decline Curve Analysis by : Peter O. Ikewun
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.
