A Comprehensive Model for Real Gas Transport in Shale Formations with Complex Non-planar Fracture Networks

A complex fracture network is generally generated during the hydraulic fracturing treatment in shale gas reservoirs. Numerous efforts have been made to model the flow behavior of such fracture networks. However, it is still challenging to predict the impacts of various gas transport mechanisms on well performance with arbitrary fracture geometry in a computationally efficient manner. We develop a robust and comprehensive model for real gas transport in shales with complex non-planar fracture network. Contributions of gas transport mechanisms and fracture complexity to well productivity and rate transient behavior are systematically analyzed. The major findings are: simple planar fracture can overestimate gas production than non-planar fracture due to less fracture interference. A “hump” that occurs in the transition period and formation linear flow with a slope less than 1/2 can infer the appearance of natural fractures. The sharpness of the “hump” can indicate the complexity and irregularity of the fracture networks. Gas flow mechanisms can extend the transition flow period. The gas desorption could make the “hump” more profound. The Knudsen diffusion and slippage effect play a dominant role in the later production time. Maximizing the fracture complexity through generating large connected networks is an effective way to increase shale gas production

A Theoretical Analysis of Pore Size Distribution Effects on Shale Apparent Permeability

Apparent permeability is an important input parameter in the simulation of shale gas production. Most apparent permeability models assume a single pore size. In this study, we develop a theoretical model for quantifying the effect of pore size distribution on shale apparent permeability. The model accounts for the nonuniform distribution of pore sizes, the rarefaction effect, and gas characteristics. The model is validated against available experimental data. Theoretical calculations show that the larger the pore radius, the larger the apparent permeability. Moreover, the apparent permeability increases with an increase in the width of pore size distribution, with this effect being much more pronounced at low pressure than at high pressure

Combination of radiotherapy and targeted therapy for HER2-positive breast cancer brain metastases

Abstract Radiotherapy and targeted therapy are essential treatments for patients with brain metastases from human epidermal growth factor receptor 2 (HER2)-positive breast cancer. However, the combination of radiotherapy and targeted therapy still needs to be investigated, and neurotoxicity induced by radiotherapy for brain metastases has also become an important issue of clinical concern. It remained unclear how to achieve the balance of efficacy and toxicity with the application of new radiotherapy techniques and new targeted therapy drugs. This article reviews the benefits and potential risk of combining radiotherapy and targeted therapy for HER2-positive breast cancer with brain metastases

Model test study of bending moment and negative skin friction for batter rock-socketed piles under surface load

Batter rock-socketed piles (BRSP) foundation is one of common foundations, such as port engineering or cross-sea bridge, while there are few studies on negative skin friction for BRSP. A series of model tests are conducted to explore negative skin friction of BRSP which are embedded in thick soft clay. The effects of the inclined angle of piles and soil consolidation time to negative friction resistance and the bending moment of BRSP are analyzed. The test results show that: the development of negative friction and bending moment BRSP have pronounced time effect; the longer the consolidation time is, the slower the axial force and bending moment intensify. The ultimate pile shaft axial force and bending moment increases nonlinearly concerning the inclined angle of piles. And the “neutral point” position and peak point of bending moment is always located at 0.9~1.0 times soil depth

Reciprocal transformations for unsupervised video object segmentation

National Natural Science Foundation of China;Natural Science Foundation of Fujian Provinc

Productivity Prediction of Fractured Horizontal Well in Shale Gas Reservoirs with Machine Learning Algorithms

Predicting shale gas production under different geological and fracturing conditions in the fractured shale gas reservoirs is the foundation of optimizing the fracturing parameters, which is crucial to effectively exploit shale gas. We present a multi-layer perceptron (MLP) network and a long short-term memory (LSTM) network to predict shale gas production, both of which can quickly and accurately forecast gas production. The prediction performances of the networks are comprehensively evaluated and compared. The results show that the MLP network can predict shale gas production by geological and fracturing reservoir parameters. The average relative error of the MLP neural network is 2.85%, and the maximum relative error is 12.9%, which can meet the demand of engineering shale gas productivity prediction. The LSTM network can predict shale gas production through historical production under the constraints of geological and fracturing reservoir parameters. The average relative error of the LSTM neural network is 0.68%, and the maximum relative error is 3.08%, which can reliably predict shale gas production. There is a slight deviation between the predicted results of the MLP model and the true values in the first 10 days. This is because the daily production decreases rapidly during the early production stage, and the production data change greatly. The largest relative errors of LSTM in this work on the 10th, 100th, and 1000th day are 0.95%, 0.73%, and 1.85%, respectively, which are far lower than the relative errors of the MLP predictions. The research results can provide a fast and effective mean for shale gas productivity prediction

A Unified Multiple Transport Mechanism Model for Gas through Shale Pores

Predicting apparent gas permeability (AGP) in nanopores is a major challenge for shale gas development. Considering the differences in the gas molecule-pore wall interactions in inorganic and organic nanopores, the gas transport mechanisms in shale remain unclear. In this paper, gas flow channels in shale, which are separated into inorganic pores and organic pores, are treated as nanotubes. Inorganic pores are assumed to be hydrophilic, and organic pores are assumed to be hydrophobic. In organic pores, multiple bulk free gas and surface adsorbed gas transport mechanisms are incorporated, while the bulk gas and water film are considered within inorganic pores. This paper presents a unified multiple transport mechanism model for both organic nanopores and inorganic nanopores. Unlike the earlier models, the presented models consider the absorption, stress dependence, real gas, and water storage effects on gas transport comprehensively for the entire flow regime. The results are validated with published data which is more in line with the real situation. The results show that (1) the AGP decreases gradually as the pore pressure decreases but that the decrease is sharp in small pores, (2) the AGP decreases dramatically when considering the real gas effect at 50 MPa in a 2 nm pore size, and (3) for a small pore size at the critical high-water saturation, AGP might increase suddenly as the flow regime changes from continuum flow to slip flow. The findings of this study can help for better understanding of the gas transport mechanisms for the entire flow regime in shale