Download or read book Informing the Modified Hyperbolic Decline Curve0 9s Minimum Decline Parameter with Numerical Simulation in Unconventional Reservoirs written by Zakary Kypfer and published by . This book was released on 2021 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: ne of the most important aspects in the life-cycle of a petroleum well is understanding, and being able to reasonably predict, the total hydrocarbon output that a well will have through its producing life. The estimation of reserves has strong economic and legal implications that will not only determine whether a well-drilling plan is viable but also the worth of a company itself. This study aims to better understand the two primary production forecasting methods used in the petroleum industry: decline curve analyses and numerical reservoir simulations, and their ability to complement one another to make a better-informed production forecast when used together. Decline curve analyses have a heavy reliance on prior hydrocarbon production data which presents difficulty in forecasting during early-term behavior due to a lack of production data; however, reservoir simulations are stronger in early well-life because they are based more heavily on reservoir parameters. The objective is to use reservoir simulations to inform the decline curve's early time behavior, by informing parameters in their equations such as Dmin, while developing a correlational relationship between the two forecasting techniques that could be applied and translated to other reservoirs in the future. A decline curve analysis was performed on a three-well study area and Dmin values of 6%, 8%, and 10% were evaluated. The matching process of the decline curves heavily relied on the cumulative production in addition to the production rates, which used a thirty-day rolling average of the daily production data. Two equivalent numerical reservoir simulation models were built for the Eagle Ford which primarily used literature sourced values for the properties. The models were history matched to the observed data very well, though each model indicated different conclusions for a suggested Dmin value. Further compounding the results, the range of uncertainty in the matrix porosity property is larger than the range of the Dmin values. Due to this, the authors are not able to use the simulation models to inform parameters in decline curve analyses nor attempt to translate that relationship to other reservoirs.

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

Download or read book 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.

Download or read book Approximate Bayesian Computation for Probabilistic Decline Curve Analysis in Unconventional Reservoirs written by Mohit Paryani and published by . This book was released on 2015 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predicting the production rate and ultimate production of shale resource plays is critical in order to determine if development is economical. In the absence of production from the Shublik Shale, Alaska, Arps' decline model and other newly proposed decline models were used to analyze production data from oil producing wells in the Eagle Ford Shale, Texas. It was found that shales violated assumptions used in Arps' model for conventional hydrocarbon accumulations. Newly proposed models fit the past production data to varying degrees, with the Logistic Growth Analysis (LGA) and Power Law Exponential (PLE) models making the most conservative predictions and those of Duong's model falling in between LGA and PLE. Using a regression coefficient cutoff of 95%, we see that the LGA model fits the production data (both rate and cumulative) from 81 of the 100 wells analyzed. Arps' hyperbolic and the LGA equation provided the most optimistic and pessimistic reserve estimates, respectively. The second part of this study investigates how the choice of residual function affects the estimation of model parameters and consequent remaining well life and reserves. Results suggest that using logarithmic rate residuals maximized the likelihood of Arps' equation having bounded estimates of reserves. We saw that approximately 75% of the well histories that were fitted using the logarithmic rate residual had hyperbolic b-values

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.

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

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

Download or read book Bulletin of the Atomic Scientists written by and published by . This book was released on 1961-05 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.

Download or read book Decline Curve Analysis for Infinite Double Porosity Systems Without Wellbore Skin written by and published by . This book was released on 1985 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents a transient pressure analysis method for analyzing the rate decline of a constant pressure well producing in an infinite double-porosity reservoir, without wellbore skin. This analysis method may be used to interpret well test rate data, and to compute the rate behavior of an infinitely acting reservoir that is being produced at constant pressure. The development of the pseudo steady state log-log type curve Is presented along with a hypothetical example of its use. This type curve allows the estimation of the two controlling parameters in double-porosity systems: [lambda] and [omega]. The first parameter, [lambda], describes the interporosity flow, and the second parameter, [omega] describes the relative fracture storativity. This paper considers the estimation of these two parameters. The estimations of permeabilities and storativities have been described in the past, hence, are not considered. In a double-porosity system, with pseudo steady state interporosity flow, the initial infinite acting rate decline, representing only the fracture system, is followed by a constant rate flow period. The length of this constant rate flow period is controlled by the parameter [omega]. The beginning of this period is controlled by the interporosity flow parameter, [lambda]. Following this constant rate period, the rate resumes an infinite homogeneous decline, representing the total system, fractures and matrix. The parameters [lambda] and [omega] may be estimated from a log-log match of rate data to the type curve. A comparison between rate responses of two transient flowing matrices and the pseudo steady state matrix Is presented. Transient interporosity flow allows the matrix to increase the well flowrate in the early and transition portions of the flow. The final decline, representing the total system, is identical to the decline with a pseudo steady state matrix.

Download or read book Decline Curve Derivative Analysis for Homogeneous and Composite Reservoirs written by and published by . This book was released on 1987 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, the rate decline and rate decline derivatives of a constant pressure well are presented for infinite, constant pressure outer boundary, and closed outer boundary homogeneous reservoirs. A rate derivative type curve is provided for these cases as well. The effects of the dimensionless reservoir exterior radius are discussed. Rate decline and rate decline derivatives of a constant pressure well in an infinite composite reservoir are also presented. For composite reservoirs, the effects of mobility ratios and discontinuity distance on both rate decline and rate decline derivatives are presented. Type curves for dimensionless wellbore flow rate derivatives for infinite composite reservoirs are provided. A new correlating group for the derivative type curve is provided, and is different than the correlating group for the rate type curve presented in the past. Finally, an analysis method that comprises type curve and derivative type curve matching to determine the dimensionless variables is proposed and demonstrated with a simulated example.

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:

Download or read book Investigation of Methods to Compensate for Downtime in Decline Curve Analysis written by Laurie Swanson and published by . This book was released on 1984 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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

Download or read book Multi phase Decline Curve Analysis with Normalized Rate and Time written by Michael Lee Fraim and published by . This book was released on 1988 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Comparison of Decline Curve Analysis Methods written by Raul Jose Rivera and published by . This book was released on 2006 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Analytics in Reservoir Engineering written by Sathish Sankaran and published by . This book was released on 2020-10-29 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering.

Download or read book Statistical Power Analysis for the Behavioral Sciences written by Jacob Cohen and published by Routledge. This book was released on 2013-05-13 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.