Investigation of Gas Slippage Effect and Geomechanical Effect on Gas Production Prediction and Hydraulic Fracture Design -- A Case Study of Marcellus Shale

2018 ◽  
Author(s):  
Courtney L. Rubin
2021 ◽  
Author(s):  
Mohamed El Sgher ◽  
Kashy Aminian ◽  
Ameri Samuel

Abstract The objective of this study was to investigate the impact of the hydraulic fracturing treatment design, including cluster spacing and fracturing fluid volume on the hydraulic fracture properties and consequently, the productivity of a horizontal Marcellus Shale well with multi-stage fractures. The availability of a significant amount of advanced technical information from the Marcellus Shale Energy and Environment Laboratory (MSEEL) provided an opportunity to perform an integrated analysis to gain valuable insight into optimizing fracturing treatment and the gas recovery from Marcellus shale. The available technical information from a horizontal well at MSEEL includes well logs, image logs (both vertical and lateral), diagnostic fracture injection test (DFIT), fracturing treatment data, microseismic recording during the fracturing treatment, production logging data, and production data. The analysis of core data, image logs, and DFIT provided the necessary data for accurate prediction of the hydraulic fracture properties and confirmed the presence and distribution of natural fractures (fissures) in the formation. Furthermore, the results of the microseismic interpretation were utilized to adjust the stress conditions in the adjacent layers. The predicted hydraulic fracture properties were then imported into a reservoir simulation model, developed based on the Marcellus Shale properties, to predict the production performance of the well. Marcellus Shale properties, including porosity, permeability, adsorption characteristics, were obtained from the measurements on the core plugs and the well log data. The Quanta Geo borehole image log from the lateral section of the well was utilized to estimate the fissure distribution s in the shale. The measured and published data were utilized to develop the geomechnical factors to account for the hydraulic fracture conductivity and the formation (matrix and fissure) permeability impairments caused by the reservoir pressure depletion during the production. Stress shadowing and the geomechanical factors were found to play major roles in production performance. Their inclusion in the reservoir model provided a close agreement with the actual production performance of the well. The impact of stress shadowing is significant for Marcellus shale because of the low in-situ stress contrast between the pay zone and the adjacent zones. Stress shadowing appears to have a significant impact on hydraulic fracture properties and as result on the production during the early stages. The geomechanical factors, caused by the net stress changes have a more significant impact on the production during later stages. The cumulative gas production was found to increase as the cluster spacing was decreased (larger number of clusters). At the same time, the stress shadowing caused by the closer cluster spacing resulted in a lower fracture conductivity which in turn diminished the increase in gas production. However, the total fracture volume has more of an impact than the fracture conductivity on gas recovery. The analysis provided valuable insight for optimizing the cluster spacing and the gas recovery from Marcellus shale.


2017 ◽  
Vol 157 ◽  
pp. 1148-1159 ◽  
Author(s):  
Thomas A. McCourt ◽  
Suzanne Hurter ◽  
Brodie Lawson ◽  
Fengde Zhou ◽  
Bevan Thompson ◽  
...  

2019 ◽  
Author(s):  
Vidya Sagar Bammidi ◽  
Millad Mortazavi ◽  
Mark McClure ◽  
Sarkis Kakadjian ◽  
Dave Sobernheim

2016 ◽  
Vol 4 (1) ◽  
pp. T15-T30 ◽  
Author(s):  
Thomas H. Wilson ◽  
Ariel K. Hart ◽  
Pete Sullivan

The data we analyzed are from a Marcellus Shale gas field in Greene County, southwestern Pennsylvania. We first investigated the relationship between microseismic event trends and discontinuities extracted from 3D seismic data and their relationship to [Formula: see text]. This analysis was followed by an examination of the relationship of cumulative gas production to radiated energy, stimulated reservoir volume (SRV), and energy density (ED). We have determined that microseismic event trends observed in multiwell hydraulic fracture treatments were similar to the trends of interpreted small faults and fracture zones extracted from 3D seismic coverage of the area. Hydraulic fracture treatments conducted in six laterals produced clusters of microseismic events with an average trend of N51°E and, to a more limited extent, N56°W. The N51°E microseismic event trend coincided closely with the average N52°E trend of interpreted minor faults and fracture zones extracted from the 3D seismic data. That relationship suggested that microseismic events form through reactivation of old faults and fracture zones in response to an easterly trending [Formula: see text]. We also found that variations in gas production correlated with variations in radiated microseismic energy ([Formula: see text] of 0.985), SRV ([Formula: see text] of 0.974), and ED ([Formula: see text] of 0.989). SRV is a measure of the volume of space occupied by induced microseismicity, whereas energy release per unit volume (ED) can be directly related to rupture area created through hydraulic fracture stimulation. We suggest that ED serves as a better estimator of production potential in unconventional shale reservoirs.


2021 ◽  
Vol 9 ◽  
Author(s):  
Huijun Wang ◽  
Lu Qiao ◽  
Shuangfang Lu ◽  
Fangwen Chen ◽  
Zhixiong Fang ◽  
...  

Shale gas production prediction and horizontal well parameter optimization are significant for shale gas development. However, conventional reservoir numerical simulation requires extensive resources in terms of labor, time, and computations, and so the optimization problem still remains a challenge. Therefore, we propose, for the first time, a new gas production prediction methodology based on Gaussian Process Regression (GPR) and Convolution Neural Network (CNN) to complement the numerical simulation model and achieve rapid optimization. Specifically, through sensitivity analysis, porosity, permeability, fracture half-length, and horizontal well length were selected as influencing factors. Second, the n-factorial experimental design was applied to design the initial experiment and the dataset was constructed by combining the simulation results with the case parameters. Subsequently, the gas production model was built by GPR, CNN, and SVM based on the dataset. Finally, the optimal model was combined with the optimization algorithm to maximize the Net Present Value (NPV) and obtain the optimal fracture half-length and horizontal well length. Experimental results demonstrated the GPR model had prominent modeling capabilities compared with CNN and Support Vector Machine (SVM) and achieved the satisfactory prediction performance. The fracture half-length and well length optimized by the GPR model and reservoir numerical simulation model converged to almost the same values. Compared with the field reference case, the optimized NPV increased by US$ 7.43 million. Additionally, the time required to optimize the GPR model was 1/720 of that of numerical simulation. This work enriches the knowledge of shale gas development technology and lays the foundation for realizing the scale-benefit development for shale gas, so as to realize the integration of geological engineering.


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