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Deterministic And Stochastic Analyses To Quantify The Reliability Of Uncertainty Estimates In Production Decline Modeling Of Shale Gas Reservoirs
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Book Synopsis Deterministic and Stochastic Analyses to Quantify the Reliability of Uncertainty Estimates in Production Decline Modeling of Shale Gas Reservoirs by : Brent L. Johanson
Download or read book Deterministic and Stochastic Analyses to Quantify the Reliability of Uncertainty Estimates in Production Decline Modeling of Shale Gas Reservoirs written by Brent L. Johanson and published by . This book was released on 2013 with total page 91 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 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 Financial Risk Management in Banking by : Shahsuzan Zakaria
Download or read book Financial Risk Management in Banking written by Shahsuzan Zakaria and published by Routledge. This book was released on 2019-08-08 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: As risk-taking is an essential part of the banking industry, banks must practise efficient risk management to ensure survival in uncertain financial climates. Banking operations are specifically affected by fluctuations in interest rates which cause financial imbalance; thus banks are now required to put in place an effective management structure that incorporates risk management efficiency measures that help mitigate the wide range of risks they face. In this book, the authors have developed a new modelling approach to determine banks’ financial risk management by offering detailed insights into the integrated approach of dollar-offset ratio and Data Envelopment Analysis (DEA), based on derivatives usage. It further analyses the efficiency measurement under stochastic DEA approaches, namely (i) Bootstrap DEA (BDEA), (ii) Sensitivity Analysis and (iii) Chance-Constrained DEA (CCDEA). As demonstrated in the modelling exercise, this integrated approach can be applied to other cases that require risk management efficiency measurement strategies. Additionally, this is the first book to comprehensively review the derivative markets of both the developed and developing countries in the Asia-Pacific region, by examining the differences of risk management efficiency of the banking institutions in these countries. Based on this measurement approach, strategies are provided for banks to improve their strategic risk management practices, as well as to reduce the impacts from external risks, such as changes in interest rates and exchange rates. Furthermore, this book will help banks to keep abreast of recent developments in the field of efficiency studies in management accounting, specifically in relation to hedge accounting, used by banks in the Asia-Pacific region.
Book Synopsis Uncertainty Analysis and Reservoir Modeling by : Y. Zee Ma
Download or read book Uncertainty Analysis and Reservoir Modeling written by Y. Zee Ma and published by AAPG. This book was released on 2011-12-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 Probabilistic Decline Curve Analysis in Unconventional Reservoirs Using Bayesian and Approximate Bayesian Inference by : Anand A. Korde
Download or read book Probabilistic Decline Curve Analysis in Unconventional Reservoirs Using Bayesian and Approximate Bayesian Inference written by Anand A. Korde and published by . This book was released on 2019 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, a probabilistic methodology for Decline Curve Analysis (DCA) in unconventional reservoirs is presented using a combination of Bayesian statistical methods and deterministic models. Accurate reserve estimation and uncertainty quantification are the primary objectives of this study. The Bayesian inferencing techniques described in this work utilizes three sampling mechanisms, namely the Gibbs Sampling (implemented in OpenBUGS), the Metropolis Algorithm, and Approximate Bayesian Computation (ABC) to sample parameter values from their posterior distributions. These different sampling mechanisms are applied in conjunction with DCA models like Arps, Power Law Exponential (PLE), Stretched Exponential Production Decline (SEPD), Duong and Logistic Growth Analysis (LGA) to estimate prediction intervals. Production is forecasted, and uncertainty bounds are established using these prediction intervals. A complete workflow and the summary steps for each of the sampling techniques are provided to permit readers to replicate results. To examine the reliability, the methodology was tested over 74 oil and gas wells located in the three main sub plays of the Permian Basin, namely, the Delaware play, the Central Basin Platform, and the Midland play. Results show that the examined DCA-Bayesian models are successful in providing a high coverage rate, low production prediction errors and narrow uncertainty bounds for the production history data sets. The methodology was also successfully applied to unconventional reservoirs with as low as 6 months of available production history. Depending on the amount of production history available, the combined deterministic-stochastic model that provides the best fit can vary. It is therefore recommended that all possible combinations of the deterministic and stochastic models be applied to the available production history data. This is in order to obtain more confidence in the conclusions related to the reserve estimates and uncertainty bounds. The novelty of this methodology relies in using multiple combinations of DCA-Bayesian models to achieve accurate reserve estimates and narrow uncertainty bounds. The paper can help assess shale plays as most of the shale plays are in the early stages of production when the reserve estimations are carried out.
Book Synopsis Uncertainty Quantification in Unconventional Reservoirs Using Conventional Bootstrap and Modified Bootstrap Methodology by : Chukwuemeka Okoli
Download or read book Uncertainty Quantification in Unconventional Reservoirs Using Conventional Bootstrap and Modified Bootstrap Methodology written by Chukwuemeka Okoli and published by . This book was released on 2020 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Various uncertainty quantication methodologies are presented using a combination of several deterministic decline curve analysis models and two bootstrapping algorithms. The bootstrapping algorithms are the conventional bootstrapping method (CBM) and the modied bootstrapping method (MBM). The combined deterministic-stochastic combination models are applied to 126 sample wells from the Permian basin. Results are presented for 12 to 72 months of production hindcast given an average well production history of 120 months. Previous researchers used the Arps model and both conventional and modied bootstrapping with block re-sampling techniques to reliably quantify uncertainty in production forecasts. In this work, we applied both stochastic techniques to other decline curve analysis models|namely, the Duong and the Stretched Exponential Production Decline (SEPD) models. The algorithms were applied to sample wells spread across the three main sub-basins of the Permian. A description of how both the deterministic and stochastic methods can be combined is provided. Also, pseudo-codes that describes the methodologies applied in this work is provided to permit readers to replicate results if necessary. Based on the average forecast error plot in the Permian Basin for 126 active wells, we can also conclude that the MBM-Arps, CBM-Arps, and MBM-SEPD combinations produce P50 forecasts that match cumulative production best regardless of the sub-basin and amount of production hindcast used. Regardless of concerns about the coverage rate, the CBM-Arps, MBM-Arps, CBM-SEPD, and MBMSEPD algorithm combinations produce cumulative P50 predictions within 20% of the true cumulative production value using only a 24-month hindcast. With a 12 month-hindcast, the MBM-Arps combined model produced cumulative P50 predictions with a forecast error of approximately 20%. Also, the CBM-SEPD and MBM-SEPD models were within 30% of the true cumulative production using a 12- month hindcast. Another important result is that all the deterministic-stochastic method combinations studied under-predicted the true cumulative production to varying degrees. However, the CBM-Duong combination was found to severely under-predict cumulative production, especially for the 12-month hindcast. It is not a suitable model combination based on forecast error, especially when hindcast fractions on the low end of the spectrum are used. Accordingly, the CBM- Duong combination is not recommended, especially if production history of no more than 24 months is available for hindcasting. As expected, the coverage rate increased, and the forecast error decreased for all the algorithm combinations with increasing hindcast duration. The novelty of this work lies in its extension of the bootstrapping technique to other decline curve analysis models. The software developed can also be used to analyze many wells quickly on a standard engineering computer. This research is also important because realistic estimates of reserves can be estimated in plays like the Permian basin when uncertainty is correctly quantied.
Book Synopsis Comparison of Various Deterministic Forecasting Techniques in Shale Gas Reservoirs with Emphasis on the Duong Method by : Krunal Jaykant Joshi
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.
Book Synopsis Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs by : James Cody Statton
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%.
Book Synopsis Evaluation of the Stretched Exponential Production Decline Model and Comparison to Other Decline Models for Shale Reservoirs by : Dong Li
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.
Book Synopsis Parameter Estimation and Uncertainty Quantification in Water Resources Modeling by : Philippe Renard
Download or read book Parameter Estimation and Uncertainty Quantification in Water Resources Modeling written by Philippe Renard and published by Frontiers Media SA. This book was released on 2020-04-22 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical models of flow and transport processes are heavily employed in the fields of surface, soil, and groundwater hydrology. They are used to interpret field observations, analyze complex and coupled processes, or to support decision making related to large societal issues such as the water-energy nexus or sustainable water management and food production. Parameter estimation and uncertainty quantification are two key features of modern science-based predictions. When applied to water resources, these tasks must cope with many degrees of freedom and large datasets. Both are challenging and require novel theoretical and computational approaches to handle complex models with large number of unknown parameters.
Book Synopsis Geostatistical Reservoir Modeling by : Michael J. Pyrcz
Download or read book Geostatistical Reservoir Modeling written by Michael J. Pyrcz and published by Oxford University Press. This book was released on 2014-04-16 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Published in 2002, the first edition of Geostatistical Reservoir Modeling brought the practice of petroleum geostatistics into a coherent framework, focusing on tools, techniques, examples, and guidance. It emphasized the interaction between geophysicists, geologists, and engineers, and was received well by professionals, academics, and both graduate and undergraduate students. In this revised second edition, Deutsch collaborates with co-author Michael Pyrcz to provide an expanded (in coverage and format), full color illustrated, more comprehensive treatment of the subject with a full update on the latest tools, methods, practice, and research in the field of petroleum Geostatistics. Key geostatistical concepts such as integration of geologic data and concepts, scale considerations, and uncertainty models receive greater attention, and new comprehensive sections are provided on preliminary geological modeling concepts, data inventory, conceptual model, problem formulation, large scale modeling, multiple point-based simulation and event-based modeling. Geostatistical methods are extensively illustrated through enhanced schematics, work flows and examples with discussion on method capabilities and selection. For example, this expanded second edition includes extensive discussion on the process of moving from an inventory of data and concepts through conceptual model to problem formulation to solve practical reservoir problems. A greater number of examples are included, with a set of practical geostatistical studies developed to illustrate the steps from data analysis and cleaning to post-processing, and ranking. New methods, which have developed in the field since the publication of the first edition, are discussed, such as models for integration of diverse data sources, multiple point-based simulation, event-based simulation, spatial bootstrap and methods to summarize geostatistical realizations.
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 A Probabilistic Workflow for Uncertainty Analysis Using a Proxy-based Approach Applied to Tight Reservoir Simulation Studies by : Marut Wantawin
Download or read book A Probabilistic Workflow for Uncertainty Analysis Using a Proxy-based Approach Applied to Tight Reservoir Simulation Studies written by Marut Wantawin and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty associated with reservoir simulation studies should be thoroughly captured during history matching process and adequately explained during production forecasts. Lacking information and limited accuracy of measurements typically cause uncertain reservoir properties in the reservoir simulation models. Unconventional tight reservoirs, for instances, often deal with complex dynamic flow behavior and inexact dimensions of hydraulic fractures that directly affect production estimation. Non-unique history matching solutions on the basis of probabilistic logic are recognized in order to avoid underestimating prediction results. Assisted history matching techniques have been widely proposed in many literature to quantify the uncertainty. However, few applications were done in unconventional reservoirs where some distinct uncertain factors could significantly influence well performance. In this thesis, a probabilistic workflow was developed using proxy-modeling approach to encompass uncertain parameters of unconventional reservoirs and obtain reliable prediction. Proxy-models were constructed by Design of Experiments (DoE) and Response Surface Methodology (RSM). As preliminary screening tools, significant parameters were identified, thus removing those that were insignificant for the reduced dimensions. Furthermore, proxy-models were systematically built to approximate the actual simulation, then sampling algorithms, e.g. Markov Chain Monte Carlo (MCMC) method, successfully estimated probabilistic history matching solutions. An iterative procedure was also introduced to gradually improve the accuracy of proxy-models at the interested region with low history matching errors. The workflow was applied to case studies in Middle Bakken reservoir and Marcellus Shale formation. In addition to estimating misfit function for the errors, proxy-models are also regressed on the simulated quantity of the measurements at various points in time, which is shown to be very useful. This alternative method was utilized in a synthetic tight reservoir model, which analyzed the impact of complex fracture network relative to instantaneous well performance at different stages. The results in this thesis show that the proxy-based approach reasonably provides simplified approximation of actual simulation. Besides, they are very flexible and practical for demonstrating the non-unique history matching solutions and analyzing the probability distributions of complicated reservoir and fracture properties. Ultimately, the developed workflow delivers probabilistic production forecasts with efficient computational requirement.
Book Synopsis Challenges in Modelling and Simulation of Shale Gas Reservoirs by : Jebraeel Gholinezhad
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.
Book Synopsis Stochastic Modeling in Hydrogeology by : J. Jaime Gómez-Hernández
Download or read book Stochastic Modeling in Hydrogeology written by J. Jaime Gómez-Hernández and published by Frontiers Media SA. This book was released on 2021-07-14 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr. Andres Alcolea is employed by Geo-Energie Suisse AG and is the funder and CEO of HydroGeoModels. All other Topic Editors declare no competing interests with regards to the Research Topic subject
