Article
Computer Science, Information Systems
Qiang Feng, Baozhi Pan, Liguo Han, Pan Zhang
Summary: The paper proposes a reverse double-difference time imaging method for locating microseismic sources, using the reverse travel time difference from adjacent receivers and the arrival time difference of the microseismic event for imaging. Two imaging conditions for single and multi-source imaging are introduced, showing the method to be stable and reliable in numerical experiments.
Article
Computer Science, Interdisciplinary Applications
Daniel Wamriew, Marwan Charara, Dimitri Pissarenko
Summary: Accurate event location in downhole microseismic monitoring largely depends on the accuracy of the reconstructed velocity model. With proper inversion approach, a deep learning approach can efficiently and accurately locate microseismic events and update the velocity model in real-time.
COMPUTERS & GEOSCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Tao Li, Bing-Rui Chen, Qing Wang, Xin-Hao Zhu, Xu Wang, Ming-Xing Xie
Summary: The paper proposes a method to calculate the sensor coordinate error threshold, analyzing the impact of sensor coordinate errors to improve the accuracy of microseismic source localization. The research results demonstrate significant differences in the sensor coordinate error threshold inside and outside the sensor array, and removing sensors with greater influence can enhance location accuracy.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Geosciences, Multidisciplinary
Wojciech Gajek, Michal Malinowski
Summary: The study highlights the impact of neglecting anisotropy in velocity models on the accuracy of microseismic event locations. It suggests that inverting anisotropy model parameters could be a solution to reducing location errors. The research demonstrates the limitations of single-stage isotropic models in terms of correct event locations and the limited gain in location accuracy when multi-stage isotropic velocity models are constructed.
JOURNAL OF APPLIED GEOPHYSICS
(2021)
Article
Engineering, Geological
Liu Liu, Shaojun Li, Yaxun Xiao, Shujie Chen, Zhaofeng Wang, Guangliang Feng, Yao Wang
Summary: Microseismic (MS) monitoring is an effective technology for rockburst disaster prevention in deeply buried tunnels. Accurate MS source location is challenging due to the changing velocity distribution of surrounding rocks. This paper presents a real-time velocity inversion strategy using drilling and blasting seismic data, allowing for improved MS location accuracy. Field experiments in China Jinping Underground Laboratory Phase II further verify the performance of the proposed MS location method.
ROCK MECHANICS AND ROCK ENGINEERING
(2023)
Article
Geochemistry & Geophysics
Bin Luo, Ariel Lellouch, Ge Jin, Biondo Biondi, James Simmons
Summary: Utilizing guided-wave dispersion for seismic inversion allows for accurate estimation of shale formation properties, including thickness, velocity, and anisotropy. Analysis of the guided waves' behavior can provide insights into the characteristics of the low-velocity shale reservoir, with a focus on thickness, S-wave velocity, and VTI parameters. The method shows promise as a novel and cost-effective strategy for in situ estimation of reservoir structure and properties.
Article
Engineering, Geological
Yi Duan, Xun Luo, Guangyao Si, Ismet Canbulat
Summary: The proposed method of seismic event location based on the Shortest Path Method and Boundary Discretisation Scheme offers higher accuracy and efficiency in seismic monitoring.
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2022)
Article
Energy & Fuels
Changpeng Yu, Yaling Zhu, Serge Shapiro
Summary: This study proposes a geology- and rock-physics-constrained approach to estimate shale anisotropy using down-hole microseismic data sets and applies it to the Horn River shale case. The optimized anisotropic velocity model improves the accuracy of data processing and the locations of events. The research also highlights the differences in fabric anisotropy between different shale gas reservoirs.
Article
Geochemistry & Geophysics
Muhammad Abid, Liping Niu, Jiqiang Ma, Jianhua Geng
Summary: The Sembar Shale formation in the Lower Indus Basin, Pakistan, is believed to hold significant potential for unconventional resources, but detailed studies quantifying this potential are lacking. By utilizing seismic characterization and well logging data, the organic matter richness, mineral composition, and brittleness of the Sembar Shale can be assessed to determine its potential as an organic shale reservoir. Integrated sensitive attributes derived from rock petrophysical, geochemical, and geomechanical parameters are correlated with P-wave impedance to characterize the Sembar Shale potential, serving as first-order indicators of organic matter, porosity, and geomechanical properties. The workflow presented in this study offers a method to evaluate the unconventional reservoir potential of the Sembar Formation in other regions of the basin.
Article
Geochemistry & Geophysics
Qiang Feng, Liguo Han, Baozhi Pan, Binghui Zhao
Summary: This article presents a method for locating microseismic sources using deep reinforcement learning. The seismic records are preprocessed using a convolutional autoencoder, and the location problem is described as a Markov decision process. The task is decomposed into three subtasks, and critical elements of deep reinforcement learning are designed. Experimental results show that the proposed method can efficiently and accurately locate microseismic sources.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Chemistry, Analytical
Tong Shen, Songren Wang, Xuan Jiang, Guili Peng, Xianguo Tuo
Summary: This paper addresses the issue of low accuracy in microseismic event localization in tunnels by proposing a source-station velocity model combined with active-source technology. The model assumes different velocities from the source to each station, greatly improving the accuracy of the time-difference-of-arrival algorithm. Comparative testing selected the MLKNN algorithm as the velocity model selection method for multiple active sources. Numerical simulation and laboratory tests showed that the source-station velocity model improved location accuracy compared to isotropic and sectional velocity models, with accuracy improvements ranging from 57.05% to 89.26%.
Article
Chemistry, Multidisciplinary
Yixiu Zhou, Liguo Han, Pan Zhang, Jingwen Zeng, Xujia Shang, Wensha Huang
Summary: In this paper, the authors propose a deep learning-based approach for precise and efficient microseismic velocity modeling. By modifying the Attention U-Net network and training it using both single-event and multi-event simulation records, the method achieves velocity modeling when dealing with inseparable microseismic records. Numerical tests demonstrate that the approach effectively uncovers latent features and patterns between microseismic records and velocity models, performing well in real-time applications and achieving high precision in modeling TTI velocity structures. It also provides reliable initial models for traditional methods.
APPLIED SCIENCES-BASEL
(2023)
Article
Geosciences, Multidisciplinary
Kaixuan Qiu
Summary: Ninety percent of China's newly proven natural gas reservoirs are unconventional resources that can be developed using multi-stage fracturing horizontal well technology. This paper presents an improved practical analytical solution for unconventional gas reservoirs. By solving the material balance equation and using integration, a real-time domain solution of rate vs. pseudo-time can be directly obtained. Five numerical cases are used to validate the accuracy of the proposed analytical solution and the derived ratio of regular/irregular region pore volume is significant for evaluating the effect of hydraulic fracturing. A field example of a multi-fractured horizontal well in a tight gas reservoir is also provided for demonstration.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Chemistry, Multidisciplinary
Dmitry Alexandrov, Umair bin Waheed, Leo Eisner
Summary: The accuracy of computed traveltimes in a velocity model is crucial for localizing microseismic events. Traditional methods introduce traveltime errors strongly dependent on wave propagation direction, resulting in significant location bias. Using a factored eikonal equation or a physics-informed neural network solver can reduce location error, but small systematic errors may still exist.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Geological
Ye Dayu, Liu Guannan, Zou Xu, Yang Yugui, Wang Fangtian, Gao Feng
Summary: The study found that the fractal seepage model is more effective than the classical cubic seepage model for investigating thermal conduction, seepage, and fracture-matrix interactions in coal seams. Permeability in coal seams increases with an increase in fractal dimension, and is inversely proportional to coal seam temperature while being directly proportional to fracture-matrix fractal dimension, maximum fracture length, and maximum pore diameter.
ROCK MECHANICS AND ROCK ENGINEERING
(2022)
