Pressure Transient Behaviors of Vertical Fractured Wells With Asymmetric Fracture Patterns

Zhang, Qiushi; Wang, Daohan; Zeng, Fanhua; Guo, Zixi; Wei, Nan

doi:10.1115/1.4045226

Cited by 5 publications

(1 citation statement)

References 31 publications

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“…Because the conventional form of phase field is based on the assumption of tension and compression symmetry, it is not applicable to rock materials [1], whose tensile and compressive strengths show significant differences [2]. To reproduce the fracture behaviors exhibiting asymmetric tension-compression characteristics, Zhou et al [3]and Wang et al [4] developed new driving force formulations, whereby Mohr-Coulomb criterion can be introduced to phase field fracture modeling. Navidtehrani et al [5][6][7] proposed a general framework for decomposing the strain energy density under multi-axial loading, which enables us to simulate compressive failure in rocks under Drucker-Prager criterion.…”

Section: Introductionmentioning

confidence: 99%

Accelerating fracture simulation with phase field methods based on Drucker-Prager criterion

Liu

Yang

2023

Front. Phys.

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The paper presents a framework for accelerating the phase field modeling of compressive failure of rocks. In this study, the Drucker-Prager failure surface is taken into account in the phase field model to characterize the tension-compression asymmetry of fractures in rocks. The degradation function that decouples the phase-field and physical length scales is employed, in order to reduce the mesh density in large structures. To evaluate the proposed approach, four numerical examples are given. The results of the numerical experiments demonstrate the accuracy and efficiency of the proposed approach in tracking crack propagation paths in rock materials under Drucker-Prager criterion.

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Section: Introductionmentioning

confidence: 99%

Accelerating fracture simulation with phase field methods based on Drucker-Prager criterion

Liu

Yang

2023

Front. Phys.

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Theoretical and Experimental Determination of Proppant Crushing Rate and Fracture Conductivity

Guo

Zhao

Guo

et al. 2020

Journal of Energy Resources Technology

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Proppant is an important material for hydraulic fracturing that impacts the production and production cost of oil and gas wells. The key properties of proppant are crushing rate and fracture conductivity. The most common way to evaluate the key properties of proppant is physical testing, but this method is time-consuming and costly, and it may result in different results under the same experimental conditions. This paper presents a method for calculating proppant crushing rate and fracture conductivity, which are obtained by combining a series of simple and economical laboratory experiments with a significant amount of numerical calculations under various experimental conditions. First, the arrangement of proppant particles was simulated, and the location of particles was determined with the Monte Carlo method, the optimization model, and search algorithm in this process. Second, by mechanical analysis of proppant particles, a mathematical model of force was established, and the singular-value decomposition (SVD) method was used to calculate the force of each particle. Third, the crushing rate of proppant particles was calculated under irregular conditions using mathematical statistics. The Kozeny–Carman equation was improved on to establish a fracture conductivity model. Finally, the average fracture conductivity was calculated on the basis of the simulation results. The calculated fracture conductivity is consistent with the experimental results, which verifies the accuracy of the model.

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A Combined Wavelet Transform and Recurrent Neural Networks Scheme for Identification of Hydrocarbon Reservoir Systems From Well Testing Signals

Moghimihanjani

Vaferi

2020

Journal of Energy Resources Technology

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Oil and gas are likely the most important sources for producing heat and energy in both domestic and industrial applications. Hydrocarbon reservoirs that contain these fuels are required to be characterized to exploit the maximum amount of their fluids. Well testing analysis is a valuable tool for characterization of hydrocarbon reservoirs. Handling and analysis of long-term and noise-contaminated well testing signals using the traditional methods is a challenging task. Therefore, in this study a novel paradigm that combines wavelet transform (WT) and recurrent neural networks (RNN) is proposed for analyzing the long-term well testing signals. The WT not only reduces dimension of the pressure derivative (PD) signals during feature extraction, but it efficiently removes noisy data. The RNN identifies reservoir type and its boundary condition from the extracted features by WT. Results confirmed that five-level decomposition of the PD signals by the Bior 1.1 filter provides the best features for classification A two-layer RNN model with 9 hidden neurons correctly detects 3202 out 3298 hydrocarbon reservoir systems. Performance of the proposed approach is checked using smooth, noisy, and real field well testing signals. Moreover, comparison is done among predictive accuracy of WT-RNN, traditional RNN, conventional multilayer perceptron (MLP) neural networks, and couple WT-MLP approaches. The results confirm that the coupled WT-RNN paradigm is superior to the other considered smart machines.

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Pressure Transient Behaviors of Vertical Fractured Wells With Asymmetric Fracture Patterns

Cited by 5 publications

References 31 publications

Accelerating fracture simulation with phase field methods based on Drucker-Prager criterion

Accelerating fracture simulation with phase field methods based on Drucker-Prager criterion

Theoretical and Experimental Determination of Proppant Crushing Rate and Fracture Conductivity

A Combined Wavelet Transform and Recurrent Neural Networks Scheme for Identification of Hydrocarbon Reservoir Systems From Well Testing Signals

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