COMBINING DECLINE CURVE ANALYSIS AND GEOSTATISTICS TO FORECAST GAS PRODUCTION IN THE MARCELLUS SHALE.

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Book Synopsis COMBINING DECLINE CURVE ANALYSIS AND GEOSTATISTICS TO FORECAST GAS PRODUCTION IN THE MARCELLUS SHALE. by : Zhenke Xi

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.

Application of Probabilistic Decline Curve Analysis to Unconventional Reservoirs

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Total Pages : 126 pages
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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.

Stretched Exponential Decline Model as a Probabilistic and Deterministic Tool for Production Forecasting and Reserve Estimation in Oil and Gas Shales

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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.

Production Optimization and Forecasting of Shale Gas Wells Using Simulation Models and Decline Curve Analysis

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Total Pages : 378 pages
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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.

Decline Curve Analysis in Unconventional Resource Plays Using Logistic Growth Models

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Total Pages : 204 pages
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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.

Probabilistic Oil and Gas Production Forecasting Using Machine Learning

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Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)

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Book Synopsis Probabilistic Oil and Gas Production Forecasting Using Machine Learning by : Robert Andrais

Download or read book Probabilistic Oil and Gas Production Forecasting Using Machine Learning written by Robert Andrais and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis improves oil- and gas-well profitability by quantifying the uncertainty of the production-forecasting process, using probabilistic machine learning (ML) techniques. A Bayesian Neural Network successfully modelled a complex shale gas reservoir system (Eagle Ford), generating a production forecast with 5% mean absolute percent error. This result is 10%-35% more accurate than traditional decline curve analysis. These forecasts also quantified the epistemic and aleatory uncertainties, providing plausible probabilistic P10 and P90 values. This range provides analysts with the capability of making informed strategic decisions that consider risk. Next, the model was applied to predict reserves (estimated ultimate recovery) and the underlying reservoir quality. These predictions were combined with unsupervised learning techniques (Gaussian Mixture Modelling), creating gas and oil sweet-spot maps. Finally, this workflow's robustness was demonstrated by artificially reducing data by 93%; indeed, the algorithm could reproduce the full-dataset results with a 71%-91% Pearson correlation, despite this reduction. Supporting this workflow creation is an evaluation of relevant research, data processing, feature engineering, documentation of the probabilistic ML structure, and discussion of model performance using systems analysis.

Application of the Stretched Exponential Production Decline Model to Forecast Production in Shale Gas Reservoirs

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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%.

A Study of Decline Curve Analysis in the Elm Coulee Field

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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

Study of the Effect of Fracture Completion Variables on Decline Curve Parameters for Long-term Production Forecast of Shale Liquids

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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.

Analysis of Production Decline Curves

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ISBN 13 : 9781555631444
Total Pages : 0 pages
Book Rating : 4.6/5 (314 download)

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Book Synopsis Analysis of Production Decline Curves by : Steven W. Poston

Download or read book Analysis of Production Decline Curves written by Steven W. Poston and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the production characteristics and associated interpretation analyses of petroleum reservoirs in a complete, thorough, and consistent manner.

Comparison of Emperical Decline Curve Analysis for Shale Wells

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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

Analysis of Shale Production Performance Using Decline Curve Methods

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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:

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

Using Decline Curve Analysis, Volumetric Analysis, and Bayesian Methodology to Quantify Uncertainty in Shale Gas Reserve Estimates

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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

Decline Curve Analysis for Real Gas Wells with Non-Darcy Flow

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Total Pages : 522 pages
Book Rating : 4.:/5 (227 download)

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Book Synopsis Decline Curve Analysis for Real Gas Wells with Non-Darcy Flow by : Michael Lee Fraim

Download or read book Decline Curve Analysis for Real Gas Wells with Non-Darcy Flow written by Michael Lee Fraim and published by . This book was released on 1989 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Analysis of Production Data from Horizontal Shale Wells Using Decline Curves

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Total Pages : 218 pages
Book Rating : 4.:/5 (937 download)

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Book Synopsis Analysis of Production Data from Horizontal Shale Wells Using Decline Curves by : Atoosa Mashayekhi

Download or read book Analysis of Production Data from Horizontal Shale Wells Using Decline Curves written by Atoosa Mashayekhi and published by . This book was released on 2014 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Decline Curve Analysis in Shale Gas Wells

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Book Synopsis Decline Curve Analysis in Shale Gas Wells by :

Download or read book Decline Curve Analysis in Shale Gas Wells written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: