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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.
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 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 Study of the Effect of Fracture Completion Variables on Decline Curve Parameters for Long-term Production Forecast of Shale Liquids by : Eshwar C. Yennigalla
Download or read book Study of the Effect of Fracture Completion Variables on Decline Curve Parameters for Long-term Production Forecast of Shale Liquids written by Eshwar C. Yennigalla and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Shale reservoir exploitation using multiple stage hydraulically fractured horizontal wells has proved the existence of considerable amount of oil and gas reserves throughout the world. Forecasts of future production from these reservoirs based on the fracture stimulation parameters and reservoir properties has led to a better understanding of the duration of important flow regimes and parameters used in production forecasting models. The decline curve analysis considered in the study is a combination of the traditional Arps and Stretched Exponential production decline models designed to fit the forecasts for individual flow regime production data. Simulations using identical reservoir properties but different fracture completion parameters were analyzed and fit to decline models. The parameters considered in our study are fracture half-length, fracture spacing, stimulated reservoir volume permeability and matrix permeability.
Book Synopsis 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 A Study of Decline Curve Analysis in the Elm Coulee Field by : Seth C Harris
Download or read book A Study of Decline Curve Analysis in the Elm Coulee Field written by Seth C Harris and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last two years, due in part to the collapse of natural gas prices, the oil industry has turned its focus from shale gas exploration to shale oil/tight oil. Some of the important plays under development include the Bakken, Eagle Ford, and Niobrara. New decline curve methods have been developed to replace the standard Arps model for use in shale gas wells, but much less study has been done to verify the accuracy of these methods in shale oil wells. The examples that I investigated were Arps with a 5% minimum decline rate as well as the stretched exponential model (SEPD) and the Duong method. There is a great amount of uncertainty about how to calculate reserves in shale reservoirs with long multi-fractured horizontals, since these wells have not yet been produced to abandonment. Although the Arps model can reliably describe conventional reservoir production decline, it is still uncertain which empirical decline curve method best describes a shale oil well to get a rapid assessment of expected recovery. My focus began in the oil window of the Eagle Ford, but I ultimately chose to study the Elm Coulee field (Bakken formation) instead to see what lessons an older tight oil play could lend to newer plays such as the Eagle Ford. Contrary to existing literature, I have found evidence from diagnostic plots that many horizontal wells in the Elm Coulee that began producing in 2006 and 2007 have entered boundary-dominated flow. In order to accommodate boundary flow I have modified the Duong and SEPD methods such that once boundary-dominated flow begins the decline is described by an Arps curve with a b-value of 0.3. What I found from hindcasting was that early production history, up to six months, is generally detrimental to accurate forecasting in the Elm Coulee. This was particularly true for the Arps with 5% minimum decline or the Duong method. Early production history often contains apparent bilinear flow or no discernible trend. There are many possible reasons for this, particularly the rapid decrease in bottomhole pressure and production of fracture fluid. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151644
Book Synopsis 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 Comparison of Emperical Decline Curve Analysis for Shale Wells by : Mohammed Sami A. Kanfar
Download or read book Comparison of Emperical Decline Curve Analysis for Shale Wells written by Mohammed Sami A. Kanfar and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This study compares four recently developed decline curve methods and the traditional Arps or Fetkovich approach. The four methods which are empirically formulated for shale and tight gas wells are: 1. Power Law Exponential Decline (PLE). 2. Stretched Exponential Decline (SEPD). 3. Duong Method. 4. Logistic Growth Model (LGM). Each method has different tuning parameters and equation forms. The main objective of this work is to determine the best method(s) in terms of Estimated Ultimate Recovery (EUR) accuracy, goodness of fit, and ease of matching. In addition, these methods are compared against each other at different production times in order to understand the effect of production time on forecasts. As a part of validation process, all methods are benchmarked against simulation. This study compares the decline methods to four simulation cases which represent the common shale declines observed in the field. Shale wells, which are completed with horizontal wells and multiple traverse highly-conductive hydraulic fractures, exhibit long transient linear flow. Based on certain models, linear flow is preceded by bilinear flow if natural fractures are present. In addition to this, linear flow is succeeded by Boundary Dominated Flow (BDF) decline when pressure wave reaches boundary. This means four declines are possible, hence four simulation cases are required for comparison. To facilitate automatic data fitting, a non-linear regression program was developed using excel VBA. The program optimizes the Least-Square (LS) objective function to find the best fit. The used optimization algorithm is the Levenberg-Marquardt Algorithm (LMA) and it is used because of its robustness and ease of use. This work shows that all methods forecast different EURs and some fit certain simulation cases better than others. In addition, no method can forecast EUR accurately without reaching BDF. Using this work, engineers can choose the best method to forecast EUR after identifying the simulation case that is most analogous to their field wells. The VBA program and the matching procedure presented here can help engineers automate these methods into their forecasting sheets. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151124
Book Synopsis Development of New Decline Model for Shale Oil Reserves by : Samit Shah
Download or read book Development of New Decline Model for Shale Oil Reserves written by Samit Shah and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis provides a new methodology to forecast ultimate recovery, based on more reliable production forecast for shale oil wells using historical production data. Compared to available decline curve methods including Arps (AIME: 160, 228-247), Valko (SPE 134231) and Duong (SPE 137748), this method is more accurate and more conservative. Production forecasts play a vital role in determining the value of oil or gas wells, and improved accuracy enhances management decisions on field development. The new, more accurate method was verified using both field data and numerical simulations. This method can potentially be used in most shale reservoirs producing single-phase liquid.
Book Synopsis Decline Curve Analysis in Unconventional Resource Plays Using Logistic Growth Models by : Aaron James Clark
Download or read book Decline Curve Analysis in Unconventional Resource Plays Using Logistic Growth Models written by Aaron James Clark and published by . This book was released on 2011 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current models used to forecast production in unconventional oil and gas formations are often not producing valid results. When traditional decline curve analysis models are used in shale formations, Arps b-values greater than 1 are commonly obtained, and these values yield infinite cumulative production, which is non-physical. Additional methods have been developed to prevent the unrealistic values produced, like truncating hyperbolic declines with exponential declines when a minimum production rate is reached. Truncating a hyperbolic decline with an exponential decline solves some of the problems associated with decline curve analysis, but it is not an ideal solution. The exponential decline rate used is arbitrary, and the value picked greatly effects the results of the forecast. A new empirical model has been developed and used as an alternative to traditional decline curve analysis with the Arps equation. The new model is based on the concept of logistic growth models. Logistic growth models were originally developed in the 1830s by Belgian mathematician, Pierre Verhulst, to model population growth. The new logistic model for production forecasting in ultra-tight reservoirs uses the concept of a carrying capacity. The carrying capacity provides the maximum recoverable oil or gas from a single well, and it causes all forecasts produced with this model to be within a reasonable range of known volumetrically available oil. Additionally the carrying capacity causes the production rate forecast to eventually terminate as the cumulative production approaches the carrying capacity. The new model provides a more realistic method for forecasting reserves in unconventional formations than the traditional Arps model. The typical problems encountered when using conventional decline curve analysis are not present when using the logistic model. Predictions of the future are always difficult and often subject to factors such as operating conditions, which can never be predicted. The logistic growth model is well established, robust, and flexible. It provides a method to forecast reserves, which has been shown to accurately trend to existing production data and provide a realistic forecast based on known hydrocarbon volumes.
Book Synopsis 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 Approximate Bayesian Computation for Probabilistic Decline Curve Analysis in Unconventional Reservoirs by : Mohit Paryani
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
Book Synopsis Better Understanding of Production Decline in Shale Gas Wells by : Kananek Harongjit
Download or read book Better Understanding of Production Decline in Shale Gas Wells written by Kananek Harongjit and published by . This book was released on 2014 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: Production data from the Eagle Ford shale (an analog to the Alaska Shublik shale) was collected from two neighboring counties and analyzed to correlate well performance with completion parameters including length of horizontal wellbore and number of hydraulic fracturing stages. Thirty-eight dry gas wells with production history range of 18-43 months were analyzed using 6 different decline curve analysis (DCA) models including Arps' exponential, harmonic and hyperbolic, power law exponential (PLE), logistic growth analysis (LGA) and Duong's models. In the matching process, 2/3 of history was used to tune the DCA models and their forecasts were compared to the remaining 1/3 of real history. The matching results were analyzed based on production history length and flow regime to have better understanding of limitations and capabilities of each DCA model. Reservoir simulation models, constructed using range of realistic data and actual completion practices of 4 select wells, were employed to assess reasonable values of remaining reserve and remaining well life that were used as benchmarks for comparison with DCA results. The results showed that there was no strong correlation between well performance (average first year production rate) and the horizontal leg or the number of fracturing stages. This was an indication of extremely heterogeneous medium. In most cases, the accuracy of the DCA models increased when longer production history was used to tune the model parameters. LGA seems to be the most accurate DCA model since it gave the highest matching accuracy 71% of the total wells when using longest history length of 31 months. As the flow regime is concerned, LGA model also performed very well matched in 57% of the wells exhibiting only transient flow and 63% for the wells showing transient flow during early production time followed by boundary-dominated flow during late production. Moreover, the remaining reserve and well life of the select wells predicted by LGA fell into reasonably close range of the estimates from the reservoir simulations.
Book Synopsis Production Decline Curves Using Data from California Oilfields by : Ralph V. Higgins
Download or read book Production Decline Curves Using Data from California Oilfields written by Ralph V. Higgins and published by . This book was released on 1971 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis U.S. Shale Oil Production and Technology Trend Estimation by : Douglas B. Reynolds
Download or read book U.S. Shale Oil Production and Technology Trend Estimation written by Douglas B. Reynolds and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scarcity and growth analyses about energy include forecasting extraction rates of non-renewable resources while taking into account technological progression. There are two distinct technological mechanisms. Moore's (1965) Law technological improvement is experience enhanced steady cost reductions. Synthesis technological change is unforeseen innovative breakthroughs. Both affect petroleum production trends differently. I analyze the two technological contributions as they relate to the Hubbert (1956 & 1962) Curve trend of extraction of U.S shale oil resources in the U.S. Lower 48 contiguous states. I build a dynamic framework for price effects, drilling rigs and the price-to-drilling rig relationship within a cointegrated, auto-regressive model.
Book Synopsis Data Analytics in Reservoir Engineering by : Sathish Sankaran
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.
