Application of probabilistic decline curve analysis to unconventional reservoirs
AuthorEgbe, Uchenna C.
KeywordOil shale reserves
Shale gas reservoirs
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AbstractThis 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.
DescriptionThesis (M.S.) University of Alaska Fairbanks, 2022
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Decline curve analysis and enhanced shale oil recovery based on Eagle Ford Shale dataDelaihdem, Dieudonne K.; Dandekar, Abhijit; Ahmadi, Mohabbat; Hanks, Catherine (2013-12)Transient and fracture dominated flow regimes in tight permeability shale reservoirs with hydraulically fractured horizontal wells impose many unconventional challenges. These include execution of appropriate shale decline curve analysis and the optimization of hydrocarbons recovery. Additionally, short production profiles available are inadequate for accurate production decline analysis. This research assessed the effectiveness of Arps' decline curve analysis and recently established methods--power law exponential analysis, logistic growth analysis, Duong's method and the author's approach--to predict future production of horizontal wells in the Eagle Ford Shale. Simulation models investigated history matching, enhanced shale oil recovery, and drainage area beyond stimulated reservoir volume. Traditional Arps' hyperbolic method sufficiently analyzed past production rates, but inaccurately forecasted cumulative productions. The recent decline models show slight variations in their past performance evaluations and forecasting future production trends. The technique proposed and used in this work enhanced the successful application of Arps' hyperbolic decline from 32.5% to 80%. Simulation results indicate 4.0% primary oil recovery factor and 5.8% enhanced shale oil recovery factor using CO��� miscible injection. Based on pressure observed outside of the stimulated reservoir volume, limited to the range of data used in this study, drainage area outside stimulated reservoir volume is not significant.
Using experimental design and response surface methodology to model induced fracture geometry in Shublik shalePoludasu, Venkatasai Sri Chand; Ahmadi, Mohabbat; Hanks, Catherine; Awoleke, Obadare (2014-12)The Triassic Shublik Formation of the Alaska North Slope is a world-class resource rock and has been identified as the major source of many of the conventional hydrocarbon accumulations on the North Slope, including Prudhoe Bay. Recent interest in the Shublik as a potential shale resource play has highlighted the need for robust hydraulic fracture modeling and simulation of the interval, but little geologic information is available because of the remote nature of the region and the complex character of the Shublik. In this study, a methodology was developed for identifying the critical variables needed for accurate planning of a hydraulic fracturing treatment in a play like the Shublik where much of the geology remains unconstrained. These identified critical variables can be used to develop a proxy model that can be used in lieu of a numerical simulator. This study was conducted in two stages. The first stage used 2-level fractional factorial design to identify the statistical significance of the input variables on the simulated fracture geometry. This stage was conducted in three phases, each phase incorporating progressively more complex assumptions about geology. Using the three most significant variables identified from first stage, the second stage of this study applies Box-Behnken experimental design and response surface methodology for quantifying functional relationships between input variables and the predicted fracture geometry. A pseudo 3D numerical simulator (Fracpro PT) and MATLAB were used to develop proxy models. These proxy models, typically a polynomial equation, are an easier alternative to Fracpro PT and can predict the fracture geometry with very less computational time. The use of experimental design drastically reduces the number of simulations required to evaluate large number of variables. With only 137 simulations, 26 variables were ranked based on their statistical significance and a non-linear proxy model was developed. Predicted values of the fracture geometry obtained using the proxy models were in good agreement with the simulated values of the fracture geometry (R2 value of 99.39% for fracture length, R2 value of 99.54% for fracture height and R2 value of 98.17% for fracture width).
Understanding reservoir engineering aspects of shale oil development on the Alaska North SlopeZanganeh, Behnam; Hanks, Catherine; Ahmadi, Mohabbat; Awoleke, Obadare (2014-05)Horizontal drilling and multi-stage hydraulic fracturing have made the commercial development of nano-darcy shale resources a success. The Shublik shale, a major source rock for hydrocarbon accumulations on the North Slope of Alaska, has huge potential for oil and gas production, with an estimated 463 million barrels of technically recoverable oil. This thesis presents a workflow for proper modeling of flow simulation in shale wells by incorporating results from hydraulic fracturing software into hydraulic fracture flow modeling. The proposed approach allows us to simulate fracture propagation and leak-off of fracturing fluid during hydraulic fracturing. This process honors the real proppant distribution, horizontal and vertical variable fracture conductivity, and presence of fracturing fluid in the fractures and surrounding matrix. Data from the Eagle Ford Shale in Texas was used for this modeling which is believed to be analogous to Alaska's Shublik shale. The performance of a single hydraulic fracture using a black oil model was simulated. Simulation results showed that for the hydraulically fractured zone, the oil recovery factor is 5.8% over thirty years of production, to an assumed economic rate of 200 STB/day. It was found that ignoring flowback overestimated oil recovery by about 17%. Assuming a constant permeability in the hydraulic fracture plane resulted in overestimation of oil recovery by almost 25%. The conductivity of the unpropped zone affected the recovery factor predictions by as much as 10%. For the case investigated, about 25% of the fracturing fluid was recovered during the first 2 months of production; in total, 44% of it was recovered over thirty years. Permeability anisotropy was found to have a significant effect on the results. These results suggest that assuming a constant conductivity for the fractures and ignoring the presence of water in the fractures and the surrounding matrix leads to overestimation of initial production rates and final recovery factors. In addition, the modified workflow developed here more accurately and seamlessly integrates the modeled induced fracture characteristics in the reservoir simulation of shale resource plays.