scholarly journals Numerical simulation by hydraulic fracturing engineering based on fractal theory of fracture extending in the coal seam

2016 ◽  
Vol 1 (4) ◽  
pp. 319-325 ◽  
Author(s):  
Xiaodong Zhang ◽  
Shuo Zhang ◽  
Yanlei Yang ◽  
Peng Zhang ◽  
Gaoyang Wei
2013 ◽  
Vol 295-298 ◽  
pp. 2980-2984
Author(s):  
Xiang Qian Wang ◽  
Da Fa Yin ◽  
Zhao Ning Gao ◽  
Qi Feng Zhao

Based on the geological conditions of 6# coal seam and 8# coal seam in Xieqiao Coal Mine, to determine reasonable entry layout of lower seam in multi-seam mining, alternate internal entry layout, alternate exterior entry layout and overlapping entry layout were put forward and simulated by FLAC3D. Then stress distribution and displacement characteristics of surrounding rock were analyzed in the three ways of entry layout, leading to the conclusion that alternate internal entry layout is a better choice for multi-seam mining, for which makes the entry located in stress reduce zone and reduces the influence of abutment pressure of upper coal seam mining to a certain extent,. And the mining practice of Xieqiao Coal Mine tested the results, which will offer a beneficial reference for entry layout with similar geological conditions in multi-seam mining.


2021 ◽  
Vol 73 (04) ◽  
pp. 60-61
Author(s):  
Chris Carpenter

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199149, “Rate-Transient-Analysis-Assisted History Matching With a Combined Hydraulic Fracturing and Reservoir Simulator,” by Garrett Fowler, SPE, and Mark McClure, SPE, ResFrac, and Jeff Allen, Recoil Resources, prepared for the 2020 SPE Latin American and Caribbean Petroleum Engineering Conference, originally scheduled to be held in Bogota, Colombia, 17–19 March. The paper has not been peer reviewed. This paper presents a step-by-step work flow to facilitate history matching numerical simulation models of hydraulically fractured shale wells. Sensitivity analysis simulations are performed with a coupled hydraulic fracturing, geomechanics, and reservoir simulator. The results are used to develop what the authors term “motifs” that inform the history-matching process. Using intuition from these simulations, history matching can be expedited by changing matrix permeability, fracture conductivity, matrix-pressure-dependent permeability, boundary effects, and relative permeability. Introduction This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 199149, “Rate-Transient-Analysis-Assisted History Matching With a Combined Hydraulic Fracturing and Reservoir Simulator,” by Garrett Fowler, SPE, and Mark McClure, SPE, ResFrac, and Jeff Allen, Recoil Resources, prepared for the 2020 SPE Latin American and Caribbean Petroleum Engineering Conference, originally scheduled to be held in Bogota, Colombia, 17-19 March. The paper has not been peer reviewed. This paper presents a step-by-step work flow to facilitate history matching numerical simulation models of hydraulically fractured shale wells. Sensitivity analysis simulations are performed with a coupled hydraulic fracturing, geomechanics, and reservoir simulator. The results are used to develop what the authors term “motifs” that inform the history-matching process. Using intuition from these simulations, history matching can be expedited by changing matrix permeability, fracture conductivity, matrix-pressure-dependent permeability, boundary effects, and relative permeability. Introduction The concept of rate transient analysis (RTA) involves the use of rate and pressure trends of producing wells to estimate properties such as permeability and fracture surface area. While very useful, RTA is an analytical technique and has commensurate limitations. In the complete paper, different RTA motifs are generated using a simulator. Insights from these motif simulations are used to modify simulation parameters to expediate and inform the history- matching process. The simulation history-matching work flow presented includes the following steps: 1 - Set up a simulation model with geologic properties, wellbore and completion designs, and fracturing and production schedules 2 - Run an initial model 3 - Tune the fracture geometries (height and length) to heuristic data: microseismic, frac-hit data, distributed acoustic sensing, or other diagnostics 4 - Match instantaneous shut-in pressure (ISIP) and wellhead pressure (WHP) during injection 5 - Make RTA plots of the real and simulated production data 6 - Use the motifs presented in the paper to identify possible production mechanisms in the real data 7 - Adjust history-matching parameters in the simulation model based on the intuition gained from RTA of the real data 8 -Iterate Steps 5 through 7 to obtain a match in RTA trends 9 - Modify relative permeabilities as necessary to obtain correct oil, water, and gas proportions In this study, the authors used a commercial simulator that fully integrates hydraulic fracturing, wellbore, and reservoir simulation into a single modeling code. Matching Fracturing Data The complete paper focuses on matching production data, assisted by RTA, not specifically on the matching of fracturing data such as injection pressure and fracture geometry (Steps 3 and 4). Nevertheless, for completeness, these steps are very briefly summarized in this section. Effective fracture toughness is the most-important factor in determining fracture length. Field diagnostics suggest considerable variability in effective fracture toughness and fracture length. Typical half-lengths are between 500 and 2,000 ft. Laboratory-derived values of fracture toughness yield longer fractures (propagation of 2,000 ft or more from the wellbore). Significantly larger values of fracture toughness are needed to explain the shorter fracture length and higher net pressure values that are often observed. The authors use a scale- dependent fracture-toughness parameter to increase toughness as the fracture grows. This allows the simulator to match injection pressure data while simultaneously limiting fracture length. This scale-dependent toughness scaling parameter is the most-important parameter in determining fracture size.


2021 ◽  
Author(s):  
Chuang Liu ◽  
Huamin Li

Abstract In the process of longwall top coal caving, the selection of the top coal caving interval along the advancing direction of the working face has an important effect on the top coal recovery. To explore a realistic top coal caving interval of the longwall top coal caving working face, longwall top coal caving panel 8202 in the Tongxin Coal Mine is used as an example, and 30 numerical simulation models are established by using Continuum-based Distinct Element Method (CDEM) simulation software to study the top coal recovery with 4.0 m, 8.0 m, 12.0 m, 16.0 m, 20.0 m and 24.0 m top coal thicknesses and 0.8 m, 1.0 m, 1.2 m, 1.6 m and 2.4 m top coal caving intervals. The results show that with an increase in the top coal caving interval, the single top coal caving amount increases. The top coal recovery is the highest with a 0.8 m top coal caving interval when the thickness of the top coal is less than 4.0 m, and it is the highest with a 1.2 m top coal caving interval when the coal seam thickness is greater than 4.0 m. These results provide a reference for the selection of a realistic top coal caving interval in thick coal seam caving mining.


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