Special Issue “Petroleum Engineering: Reservoir Fracturing Technology and Numerical Simulation”

Guo, Tiankui; Chen, Ming

doi:10.3390/pr11010233

Cited by 1 publication

(1 citation statement)

References 15 publications

(15 reference statements)

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“…The methodology allows for a comprehensive assessment of qualitative risks, using the combined fault tree and event tree to represent multiple scenarios. The risk assessments rely on the Bayesian belief network (see Figure 5) [15][16][17][18].…”

Section: Formulation Hazard Identification and Development Of An Faul...mentioning

confidence: 99%

A Bayesian Network Model for Risk Management during Hydraulic Fracturing Process

Badjadi,

Zhu,

Zhang

et al. 2023

Water

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The escalating production of shale gas and oil, witnessed prominently in developed nations over the past decade, has sparked interest in prospective development, even in developing countries like Algeria. However, this growth is accompanied by significant opposition, particularly concerning the method of extraction: hydraulic fracturing, or ‘fracking’. Concerns regarding its environmental impact, water contamination, greenhouse gas emissions, and potential health effects have sparked widespread debate. This study thoroughly examines these concerns, employing an innovative approach to assess the risks associated with hydraulic fracturing operations in shale gas reservoirs. Through the integration of diverse data sources, including quantitative and qualitative data, observational records, expert judgments, and global sensitivity analysis using the Sobol method, a comprehensive risk assessment model, was developed. This model carefully considered multiple condition indicators and extreme working conditions, such as pressures exceeding 110 MPa and temperatures surpassing 180° F. The integration of these varied data streams enabled the development of a robust Bayesian belief network. This network served as a powerful tool for the accurate identification of process vulnerabilities and the formulation of optimal development strategies. Remarkably, this study’s results showed that this approach led to a notable 12% reduction in operational costs, demonstrating its practical efficacy. Moreover, this study subjected its model to rigorous uncertainty and sensitivity analyses, pinpointing the most severe risks and outlining optimal measures for their reduction. By empowering decision-makers to make informed choices, this methodology not only enhances environmental sustainability and safety standards but also ensures prolonged well longevity while maximizing productivity in hydraulic fracturing operations.

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Section: Formulation Hazard Identification and Development Of An Faul...mentioning

confidence: 99%

A Bayesian Network Model for Risk Management during Hydraulic Fracturing Process

Badjadi,

Zhu,

Zhang

et al. 2023

Water

View full text Add to dashboard Cite

show abstract

Special Issue “Petroleum Engineering: Reservoir Fracturing Technology and Numerical Simulation”

Abstract: Hydraulic fracturing is a technique that can provide space for oil and gas flow by pumping fracturing fluid into a reservoir to fracture rock and filling proppant to create fractures or fracture nets [...]

Cited by 1 publication

References 15 publications

A Bayesian Network Model for Risk Management during Hydraulic Fracturing Process

A Bayesian Network Model for Risk Management during Hydraulic Fracturing Process

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