Numerical Analysis of the Effects of Apparent-Permeability Modeling and Secondary-Fracture Distribution for Hydraulic-Fractured Shale-Gas Production Analysis

2020 ◽  
Vol 23 (04) ◽  
pp. 1233-1250
Author(s):  
Chuanyao Zhong ◽  
Juliana Y. Leung
Keyword(s):  
Numerical Analysis ◽  
Shale Gas ◽  
Gas Production ◽  
Apparent Permeability ◽  
Secondary Fracture ◽  
Permeability Modeling ◽  
Production Analysis ◽  
Fracture Distribution

scholarly journals Triple-Porosity Modelling for the Simulation of Multiscale Flow Mechanisms in Shale Reservoirs

Geofluids ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Mingyao Wei ◽  
Jishan Liu ◽  
Derek Elsworth ◽  
Enyuan Wang
Keyword(s):  
Shale Gas ◽  
History Matching ◽  
Gas Transport ◽  
Gas Production ◽  
Natural Fracture ◽  
System Matrix ◽  
Fracture Permeability ◽  
Gas Reservoir ◽  
Apparent Permeability ◽  
Shale Reservoir

Shale gas reservoir is a typical type of unconventional gas reservoir, primarily because of the complex flow mechanism from nanoscale to macroscale. A triple-porosity model (M3 model) comprising kerogen system, matrix system, and natural fracture system was presented to describe the multispace scale, multitime scale, and multiphysics characteristic of gas flows in shale reservoir. Apparent permeability model for real gas transport in nanopores, which covers flow regime effect and geomechanical effect, was used to address multiscale flow in shale matrix. This paper aims at quantifying the shale gas in different scales and its sequence in the process of gas production. The model results used for history matching also showed consistency against gas production data from the Barnett Shale. It also revealed the multispace scale process of gas production from a single well, which is supplied by gas transport from natural fracture, matrix, and kerogen sequentially. Sensitivity analysis on the contributions of shale reservoir permeability in different scales gives some insight as to their importance. Simulated results showed that free gas in matrix contributes to the main source of gas production, while the performance of a gas shale well is strongly determined by the natural fracture permeability.

Coupled Hydro-Mechanical Analysis of Gas Production in Fractured Shale Reservoir by Random Fracture Network Modeling

2019 ◽  
Vol 11 (03) ◽  
pp. 1950031
Author(s):  
Rui Yang ◽  
Tianran Ma ◽  
Weiqun Liu ◽  
Yijiao Fang ◽  
Luyi Xing
Keyword(s):  
Network Model ◽  
Shale Gas ◽  
Fracture Network ◽  
Gas Production ◽  
Gas Reservoir ◽  
Secondary Fracture ◽  
Shale Gas Reservoir ◽  
Main Fracture ◽  
Shale Reservoir ◽  
Random Fracture

Accurate construction of a shale-reservoir fracture network is a prerequisite for optimizing the fracturing methods and determining shale-gas extraction schemes. Considering the influence of geological conditions, stress levels, desorption–adsorption, and fissure characteristics and distribution, establishing a shale-gas reservoir fracture-network model based on a random fracture network is significant. According to the discrete network model and Monte Carlo stochastic theory, the random fracture network of natural and artificial fractures in a shale-gas reservoir stimulation zone was constructed in this study. The porosity and permeability of the stimulation zone were calculated according to the network geometric properties. The fracture network was reconstructed, and the fissure connectivity was characterized. Numerical simulation of the seepage flow was performed for shale-gas reservoirs with different fracking-fracture combinations. The results showed that the local permeability dominated by the main fracture was the main factor that affected the initial shale-gas production efficiency. The total shale-gas productivity was mainly controlled by the effective stimulated volume. The evenly distributed secondary fracture network could effectively improve the effective stimulated volume of the stimulation zone. A 4% increase in the effective stimulated volume could improve the accumulated gas production by approximately 12%. Moreover, when the ratio of the main fracture to the secondary fracture was approximately 1:14, the accumulated gas production was optimized.

scholarly journals Effect of gas adsorption-induced pore radius and effective stress on shale gas permeability in slip flow: New Insights

2019 ◽  
Vol 11 (1) ◽  
pp. 948-960 ◽  
Author(s):  
Asadullah Memon ◽  
Aifen Li ◽  
Wencheng Han ◽  
Weibing Tian
Keyword(s):  
Effective Stress ◽  
Shale Gas ◽  
Pore Radius ◽  
Gas Adsorption ◽  
Gas Permeability ◽  
Slip Flow ◽  
Flow Regimes ◽  
Gas Production ◽  
Adsorption Parameters ◽  
Apparent Permeability

Abstract Shale, a heterogeneous and extremely complex gas reservoir, contains low porosity and ultra-Low permeability properties at different pore scales. Its flow behaviors are more complicated due to different forms of flow regimes under laboratory conditions. Flow regimes change with respect to pore scale variation resulting in change in gas permeability. This work presents new insights regarding the change of pore radius due to gas adsorption, effective stress and impact of both on shale gas permeability measurements in flow regimes. From this study, it was revealed that the value of Klinkenberg coefficient has been affected due to gas adsorption-induced pore radius thickness impacts and resulting change in gas permeability. The gas permeability measured from new proposed equation is provides better results as compare to existing equation. Adsorption parameters are the key factors that affect radius of shale pore. Both adsorption and effective stress have an effect on the pore radius and result gas permeability change. It was found that slip effect enhances the apparent gas permeability and also changes with effective stress; therefore, combine impact of slip flow and effective stress is very important as provides understanding in evolution of apparent permeability during shale gas production.

A NEW FRACTAL TRANSPORT MODEL OF SHALE GAS RESERVOIRS CONSIDERING MULTIPLE GAS TRANSPORT MECHANISMS, MULTI-SCALE AND HETEROGENEITY

Fractals ◽  
2018 ◽  
Vol 26 (06) ◽  
pp. 1850096 ◽  
Author(s):  
WEIPENG FAN ◽  
HAI SUN ◽  
JUN YAO ◽  
DONGYAN FAN ◽  
KAI ZHANG
Keyword(s):  
Shale Gas ◽  
Gas Flow ◽  
Knudsen Diffusion ◽  
Gas Production ◽  
Transport Mechanisms ◽  
Apparent Permeability ◽  
Multi Scale ◽  
Inorganic Systems ◽  
Inorganic Matter ◽  
Fractal Characteristics

Duo to different transport mechanisms and gas storage in organic and inorganic systems, a new triple-continuum model coupling Discrete Fracture Model (DFM) was established to investigate gas flow in shale gas reservoir. Considering the multi-scale and heterogeneity of shale matrix, fractal theory was used to calculate the apparent permeability of organic and inorganic systems while multiple gas transport mechanisms such as viscous flow, Knudsen diffusion, surface diffusion, gas absorption/desorption effect and real gas effect were incorporated. This coupled mathematical model was solved by Finite Element Method (FEM) and the presented fractal apparent permeability model was validated with the experimental data. The results show that fractal characteristics of shale matrix have great impact on gas reservoir performance. The model without considering the influence of fractal characteristics could lead to underestimate gas production by approximately 17%. Viscous flow is the dominate transport mechanisms of shale gas and Knudsen diffusion has an impact on gas flow when the pressure declines. Surface diffusion should be only considered in organic systems and can be ignored. Then the results of sensitivity analysis show that the characteristic parameters of inorganic matter have a greater impact than those of organic matter and establishing a triple-continuum model with considering comprehensive effect of organic and inorganic matter is necessary. In addition, gas production would decrease as the pore fractal dimension and tortuosity fractal dimension increase, which results from the increasing number of small pores and more tortuous path for gas flow.

scholarly journals New Hybrid Approach for Developing Automated Machine Learning Workflows: A Real Case Application in Evaluation of Marcellus Shale Gas Production

Fuels ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 286-303
Author(s):  
Vuong Van Pham ◽  
Ebrahim Fathi ◽  
Fatemeh Belyadi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Shale Gas ◽  
Field Data ◽  
Marcellus Shale ◽  
Hybrid Approach ◽  
Gas Production ◽  
Bayesian Optimization ◽  
Real Field ◽  
Engineering Problems

The success of machine learning (ML) techniques implemented in different industries heavily rely on operator expertise and domain knowledge, which is used in manually choosing an algorithm and setting up the specific algorithm parameters for a problem. Due to the manual nature of model selection and parameter tuning, it is impossible to quantify or evaluate the quality of this manual process, which in turn limits the ability to perform comparison studies between different algorithms. In this study, we propose a new hybrid approach for developing machine learning workflows to help automated algorithm selection and hyperparameter optimization. The proposed approach provides a robust, reproducible, and unbiased workflow that can be quantified and validated using different scoring metrics. We have used the most common workflows implemented in the application of artificial intelligence (AI) and ML in engineering problems including grid/random search, Bayesian search and optimization, genetic programming, and compared that with our new hybrid approach that includes the integration of Tree-based Pipeline Optimization Tool (TPOT) and Bayesian optimization. The performance of each workflow is quantified using different scoring metrics such as Pearson correlation (i.e., R2 correlation) and Mean Square Error (i.e., MSE). For this purpose, actual field data obtained from 1567 gas wells in Marcellus Shale, with 121 features from reservoir, drilling, completion, stimulation, and operation is tested using different proposed workflows. A proposed new hybrid workflow is then used to evaluate the type well used for evaluation of Marcellus shale gas production. In conclusion, our automated hybrid approach showed significant improvement in comparison to other proposed workflows using both scoring matrices. The new hybrid approach provides a practical tool that supports the automated model and hyperparameter selection, which is tested using real field data that can be implemented in solving different engineering problems using artificial intelligence and machine learning. The new hybrid model is tested in a real field and compared with conventional type wells developed by field engineers. It is found that the type well of the field is very close to P50 predictions of the field, which shows great success in the completion design of the field performed by field engineers. It also shows that the field average production could have been improved by 8% if shorter cluster spacing and higher proppant loading per cluster were used during the frac jobs.

NANOSCALE PORE SIZE DISTRIBUTION EFFECTS ON GAS PRODUCTION FROM FRACTAL SHALE ROCKS

Fractals ◽  
2019 ◽  
Vol 27 (08) ◽  
pp. 1950142
Author(s):  
JINZE XU ◽  
KELIU WU ◽  
RAN LI ◽  
ZANDONG LI ◽  
JING LI ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Pore Size Distribution ◽  
Pore Size ◽  
Size Distribution ◽  
Gas Transport ◽  
Gas Production ◽  
Lower Sensitivity ◽  
Apparent Permeability ◽  
Transport Efficiency ◽  
Nanoscale Pore

Effect of nanoscale pore size distribution (PSD) on shale gas production is one of the challenges to be addressed by the industry. An improved approach to study multi-scale real gas transport in fractal shale rocks is proposed to bridge nanoscale PSD and gas filed production. This approach is well validated with field tests. Results indicate the gas production is underestimated without considering a nanoscale PSD. A PSD with a larger fractal dimension in pore size and variance yields a higher fraction of large pores; this leads to a better gas transport capacity; this is owing to a higher free gas transport ratio. A PSD with a smaller fractal dimension yields a lower cumulative gas production; this is because a smaller fractal dimension results in the reduction of gas transport efficiency. With an increase in the fractal dimension in pore size and variance, an apparent permeability-shifting effect is less obvious, and the sensitivity of this effect to a nanoscale PSD is also impaired. Higher fractal dimensions and variances result in higher cumulative gas production and a lower sensitivity of gas production to a nanoscale PSD, which is due to a better gas transport efficiency. The shale apparent permeability-shifting effect to nanoscale is more sensitive to a nanoscale PSD under a higher initial reservoir pressure, which makes gas production more sensitive to a nanoscale PSD. The findings of this study can help to better understand the influence of a nanoscale PSD on gas flow capacity and gas production.

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