Effect of Rock Elastic Anisotropy on Hydraulic Fracture Containment in the Bakken Formation

Fracture-driven interaction FDI (colloquially called “Frac-hit”) is the interference of fractures between two or more wells. This interference can have a significant impact on well production, depending on the unconventional play of interest (which can be positive or negative). In this work, the surrogate model was used along with metaheuristic optimization algorithms to optimize the completion design for a case study in the Bakken. A numerical model was built in a physics-based simulator that combines hydraulic fracturing, geomechanics, and reservoir numerical modeling as a continuous simulation. The stress was estimated using the anisotropic extended Eaton method. The fractures were calibrated using Microseismic Depletion Delineation (MDD) and microseismic events. The reservoir model was calibrated to 10 years of production data and bottom hole pressure by adjusting relative permeability curves. The stress changes due to depletion were calibrated using recorded pressure data from MDD and FDI. Once the model was calibrated, sensitivity analysis was run on the injected volumes, the number of clusters, the spacing between clusters, and the spacing between wells using Sobol and Latin Hypercube sampling. The results were used to build a surrogate model using an artificial neural network. The coefficient of correlation was in the order of 0.96 for both training and testing. The surrogate model was used to construct a net present value model for the whole system, which was then optimized using the Grey Wolf algorithm and the Particle Swarm Optimization algorithm, and the optimum design was reported. The optimum design is a combination of wider well spacing (1320 ft), tighter cluster spacing (22 ft), high injection volume (1950 STB/cluster), and a low cluster number per stage (seven clusters). This study suggests an optimum design for a horizontal well in the Bakken drilled next to a well that has been producing for ten years. The design can be deployed in new wells that are drilled next to depleted wells to optimize the system’s oil production.

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“…for transverse isotropic media [55]. The approach assumes that the overburden's stress is applied instantaneously to an elastic rock.…”

Section: Discussionmentioning

confidence: 99%

“…The mechanical earth model was built using the anisotropic extended Eaton method for transverse isotropic media [55]. The approach assumes that the overburden's stress is applied instantaneously to an elastic rock.…”

Section: Conflicts Of Interestmentioning

confidence: 99%

Offset Well Design Optimization Using a Surrogate Model and Metaheuristic Algorithms: A Bakken Case Study

Merzoug

Rasouli

2023

Eng

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“…Unfortunately, well logs cannot depict the variation observed in Figure 1 due to the low resolution of the logging tools and the high heterogeneity of the petrophysical and geological properties, which vary from one lithofacies to another [18,19]. Mineralogy also plays a substantial role in the characterization challenges [20][21][22] as the MBM has up to eight minerals, which consist of quartz, calcite, dolomite, illite, kaolinite, K-Feldspar, Muscovite, and plagioclase, where illite, kaolinite, dolomite, and calcite play the role of the cementing materials. This makes the characterization of the mineralogy along with the Sw challenging and the use of conventional methods inaccurate due to the linear models used for mineralogy estimation and the dependence of the Archie equation on the lithology variation [21].…”

Section: Geological Settingsmentioning

confidence: 99%

Water Saturation Prediction in the Middle Bakken Formation Using Machine Learning

Mellal,

Latrach,

Rasouli

et al. 2023

Eng

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Tight reservoirs around the world contain a significant volume of hydrocarbons; however, the heterogeneity of these reservoirs limits the recovery of the original oil in place to less than 20%. Accurate characterization is therefore needed to understand variations in reservoir properties and their effects on production. Water saturation (Sw) has always been challenging to estimate in ultra-tight reservoirs such as the Bakken Formation due to the inaccuracy of resistivity-based methods. While machine learning (ML) has proven to be a powerful tool for predicting rock properties in many tight formations, few studies have been conducted in reservoirs of similar complexity to the Bakken Formation, which is an ultra-tight, multimineral, low-resistivity reservoir. This study presents a workflow for Sw prediction using well logs, core data, and ML algorithms. Logs and core data were gathered from 29 wells drilled in the Bakken Formation. Due to the inaccuracy and lack of robustness of the tried and tested regression models (e.g., linear regression, random forest regression) in predicting Sw as a continuous variable, the problem was reformulated as a classification task. Instead of exact values, the Sw predictions were made in intervals of 10% increments representing 10 classes from 0% to 100%. Gradient boosting and random forest classifiers scored the best classification accuracy, and these two models were used to construct a voting classifier that achieved the best accuracy of 85.53%. The ML model achieved much better accuracy than conventional resistivity-based methods. By conducting this study, we aim to develop a new workflow to improve the prediction of Sw in reservoirs where conventional methods have poor performance.

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“…Hydraulic fracturing fluids: In hydraulic fracturing operations, large volumes of water, sand, and chemicals are mixed and pumped into the well to create fractures in the reservoir rock as stated by Chellal et al [50]. The production, transportation, and disposal of these fluids generate CO 2 emissions [51].…”

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confidence: 99%

A Comprehensive Review of Fishbone Well Applications in Conventional and Renewable Energy Systems in the Path towards Net Zero

Ndulue,

Tomomewo,

Khalifa

2023

Fuels

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Fishbone drilling (FbD) involves drilling multiple micro-holes branching out in various directions from the primary vertical or deviated wellbore. FbD is similar to multilateral micro-hole drilling and can be employed to boost hydrocarbon production in naturally fractured formations or during refracturing operations by connecting existing natural fractures. Key design elements in fishbones include determining the number, length, and spacing between the branches, and the angle at which the branches deviate from the main borehole. Fishbone wells have emerged as a promising technology for improving well performance and reducing environmental impact. In this paper, we present a comprehensive review of the different applications of fishbone wells in conventional and renewable energy systems. We discuss the potential of fishbone wells for enhanced oil and gas recovery, as well as their application in unconventional resources such as coal bed methane. Moreover, we examine the feasibility of fishbone wells in renewable energy systems, such as geothermal energy and carbon capture, utilization, and storage (CCUS). We highlight the various benefits of fishbone wells, including reduced carbon footprint, enhanced efficiency, and increased sustainability. Finally, we discuss the challenges and limitations associated with fishbone wells in different energy systems. This review provides a comprehensive overview of the potential and challenges of fishbone wells in reducing carbon footprint and improving well performance in a wide range of energy systems.

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Effect of Rock Elastic Anisotropy on Hydraulic Fracture Containment in the Bakken Formation

Cited by 4 publications

References 0 publications

Offset Well Design Optimization Using a Surrogate Model and Metaheuristic Algorithms: A Bakken Case Study

Offset Well Design Optimization Using a Surrogate Model and Metaheuristic Algorithms: A Bakken Case Study

Water Saturation Prediction in the Middle Bakken Formation Using Machine Learning

A Comprehensive Review of Fishbone Well Applications in Conventional and Renewable Energy Systems in the Path towards Net Zero

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