Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Bessa, Fadila; Jerath, Kanay; Ginn, Chris; Johnston, P; Zhao, Yu; Brown, Tim; López, Rubén Álvaro; Kessler, James; Nicklen, Brian Lee; Sahni, Vinay

doi:10.15530/urtec-2021-5243

Cited by 5 publications

(2 citation statements)

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“…Although it is generally believed that, due to the existence of stress shadow, only a few fractures or even only one fracture can develop to the far end in one cluster of perforations, researchers who conducted studies at the Hydraulic Fracturing Test Site (HFTS) found that multiple fractures can be formed in one cluster zone. Thus, they proposed the concept of fracture swarms [9][10][11]. Ciezobka, Reeves, et al [12] conducted hydraulic fracturing research experiments at the Midland Basin in West Texas and found that up to 6-8 hydraulic fractures exist in a 1-2 foot fracturing area.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Mechanism of Fracture Initiation and Propagation under Multi-Perforation Conditions in Hydraulic Fracturing

Ding,

Xiong,

Guo

et al. 2024

Processes

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To reveal the mechanism of hydraulic fracture initiation and propagation under the conditions of multiple perforations during horizontal well fracturing, we creatively conducted dual-hole fracturing experiments on small rock samples and established a two-dimensional model of a single cluster with multiple perforations in a horizontal well based on the extended finite element method using the fluid–solid coupling equation, which was combined with the basic theory of damage mechanics. The biggest difference from previous research is that this model does not consider the hypothesis of stress shadows and only focuses on studying the initiation and propagation of multiple perforations in one cluster. We studied the effects of perforation parameters, stress state, and injection flow rate on the initiation and propagation of hydraulic fractures using this model. The experimental and simulation results indicate that under multi-perforation conditions, the number of fractures depends on the number of perforations. The simulation results show that when the spacing between perforations increases or the number of perforations reduces, the initiation time of perforation is advanced and the interference between fractures weakens, which is conducive to the initiation and propagation of hydraulic fractures. As the stress difference increases, the initiation time of perforation becomes earlier and the deflection angle of the outermost fractures becomes smaller, which is conducive to the parallel expansion of the fractures. Moreover, although this has little impact on the morphology of fractures with the rise in flow rate in simulation, it is beneficial for improving the initiation and propagation speed of fractures. The length of fractures also increases significantly at the same time point. In addition, both the experiments and simulations revealed that an increase in the flow rate could accelerate the initiation time of fractures. The proposed model can guide fracturing construction to optimize the design of perforation spacing during horizontal well fracturing, which can contribute to reducing development costs and improving the final production.

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Section: Introductionmentioning

confidence: 99%

A Study on the Mechanism of Fracture Initiation and Propagation under Multi-Perforation Conditions in Hydraulic Fracturing

Ding,

Xiong,

Guo

et al. 2024

Processes

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“…Among these techniques, coring operations are crucial to identify reservoir rock fractures (Rajabi et al, 2021;Sipahi and Develi, 2021). This operation is so costly that it is done only in some limited reservoirs and is extremely rare (Bessa et al, 2021). This paper attempts to use low-cost petrophysical logs, which are required in all wells as part of the drilling process, as well as four newly developed artificial intelligence hybrid algorithms.…”

Section: Introductionmentioning

confidence: 99%

Prediction of fracture density in a gas reservoir using robust computational approaches

Gao

Hazbeh²,

Davoodi³

et al. 2023

Front. Earth Sci.

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One of the challenges that reservoir engineers, drilling engineers, and geoscientists face in the oil and gas industry is determining the fracture density (FVDC) of reservoir rock. This critical parameter is valuable because its presence in oil and gas reservoirs boosts productivity and is pivotal for reservoir management, operation, and ultimately energy management. This valuable parameter is determined by some expensive operations such as FMI logs and core analysis techniques. As a result, this paper attempts to predict this important parameter using petrophysics logs routinely collected at oil and gas wells and by applying four robust computational algorithms and artificial intelligence hybrids. A total of 6067 data points were collected from three gas wells (#W1, #W2, and #W3) in one gas reservoir in Southwest Asia. Following feature selection, the input variables include spectral gamma ray (SGR); sonic porosity (PHIS); potassium (POTA); photoelectric absorption factor (PEF); neutron porosity (NPHI); sonic transition time (DT); bulk density (RHOB); and corrected gamma ray (CGR). In this study, four hybrids of two networks were used, including least squares support vector machine (LSSVM) and multi-layer perceptron (MLP) with two optimizers particle swarm optimizer (PSO) and genetic algorithm (GA). Four robust hybrid machine learning models were applied, and these are LSSVM-PSO/GA and MLP-PSO/GA, which had not previously used for prediction of FVDC. In addition, the k-fold cross validation method with k equal to 8 was used in this article. When the performance accuracy of the hybrid algorithms for the FVDC prediction is compared, the revealed result is LSSVM-PSO > LSSVM-GA > MLP-PSO > MLP-GA. The study revealed that the best algorithm for predicting FVDC among the four algorithms is LSSVM-PSO (for total dataset RMSE = 0.0463 1/m; R2 = 0.9995). This algorithm has several advantages, including: 1) lower adjustment parameters, 2) high search efficiency, 3) fast convergence speed, 4) increased global search capability, and 5) preventing the local optimum from falling. When compared to other models, this model has the lowest error.

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Study of the evolution characteristics of fiber-optic strain induced by the propagation of bedding fractures in hydraulic fracturing

Wang,

Chen,

et al. 2024

Petroleum Science

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Subsurface Characterization of Hydraulic Fracture Test Site-2 (HFTS-2), Delaware Basin

Cited by 5 publications

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A Study on the Mechanism of Fracture Initiation and Propagation under Multi-Perforation Conditions in Hydraulic Fracturing

A Study on the Mechanism of Fracture Initiation and Propagation under Multi-Perforation Conditions in Hydraulic Fracturing

Prediction of fracture density in a gas reservoir using robust computational approaches

Study of the evolution characteristics of fiber-optic strain induced by the propagation of bedding fractures in hydraulic fracturing

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