Hidden Faults Research Articles

Deep learning-based proactive fault detection method for enhanced quadrotor safety

The early detection of faults in advanced technological systems is imperative for ensuring operational reliability and safety. While there is a growing interest in using artificial intelligence for fault detection, current methodologies often exhibit limitations in utilizing comprehensive system information and sensor data. Hidden faults within collected data further highlight the need for advanced analysis techniques. This study introduces a novel deep learning-based framework designed to predict faults and extract insights from complex system datasets. The model, consisting of LSTM-autoencoder and BiLSTM classification components, effectively reduces feature dimensions, thereby enhancing fault detection accuracy. The autoencoder’s latent layer identifies prominent features across various dimensions, while BiLSTM classification conducts bidirectional analysis using these features from both healthy and faulty states, facilitating early fault detection. Experimental results demonstrate the model’s efficacy, achieving an accuracy of 79.48% in predicting incipient faults 30 seconds before a serious malfunction occurs. This underscores the significant potential of the proposed framework in enhancing operational safety and reliability in complex systems. Moreover, the study emphasizes the importance of leveraging comprehensive data and advanced analysis techniques for early fault detection.

Fluid‐Driven Seismicity in the Baihetan Reservoir Area Revealed by 3D Seismic Tomography Based on Dense Seismic Arrays

AbstractAfter impounding the Baihetan Water Reservoir in a historically seismically active area, numerous earthquakes occurred, but it is uncertain if they are connected to the impoundment. Based on the dense seismic network, this study used local earthquake tomography to construct high‐resolution VP (P‐wave velocity) and VP/VS models (P‐ to S‐wave velocity ratio) and update earthquake locations after the impoundment of Baihetan reservoir. Our study revealed that the reservoir water spreads from the dam site to the Qiaojia Basin and the Heishuihe branch, and pore pressure diffusion along faults induces many earthquakes. Reservoir water migrates through hidden faults and fractures beneath Hulukou, spreading to both sides and saturating some rocks below 7 km beneath the dam site‐Lianhuatang section, causing multiple magnitude 3.5+ earthquakes. This study reveals that reservoir water migration drives earthquakes in the reservoir area, offering new insights into seismogenesis following the Baihetan reservoir's impoundment, potentially applicable to understanding reservoir‐induced earthquakes in other reservoirs.

Analysis on numerical simulation and fracture mechanics model of water inrush of floor with hidden faults under dynamic and static loads

The mining activation of hidden faults under dynamic and static loads is an important reason for the occurrence of floor water inrush disasters in deep coal seam mining. The formation and evolution mechanism of water inrush channel caused by mining on the floor of hidden faults were analyzed through numerical simulation, from the perspective of fracture mechanics, a model was constructed to explore the influence of combined dynamic and static loads on the propagation of water with cracks. A conclusion was drawn that the effects of mining stress and confined water have led to rapid expansion of hidden fault cracks and significant improvement in permeability, at the same time, the confined water in the hidden fault also has a scouring and expansion effect on the cracks, accelerating their development speed. There are spatial and temporal differences in the penetration patterns of hidden faults at different positions of floor, and the closer it is to the goaf, the more likely it is to experience activation of hidden faults and water inrush. When there are multiple hidden small faults in the floor, there is an alternating change between the water inrush growth area and the flow stable area with similar cyclic characteristics. The effect of dynamic load will increase the pore pressure in cracks, and increase the stress intensity factor at the crack tip, and more easily induce crack expansion and penetration failure. The critical water pressure calculation equation for crack propagation and failure under dynamic and static loads was derived, and the calculation method for the minimum safe thickness of the floor was further analyzed, the influence of water pressure, crack length, inclination angle, and mining depth on it was discussed. The effect of dynamic load will increase the pore pressure in cracks, and increase the stress intensity factor at the crack tip, and more easily induce crack expansion and penetration failure. Finally, the theoretical analysis results were verified by an engineering examples. The research results can provide theoretical basis for predicting and preventing water inrush from the mining floor, which is beneficial for the safe and sustainable mining of coal mines.

Design of On-line Monitoring and Fault Diagnosis Platform for Oil-immersed Shunt Reactor

Abstract With the development of society and technology, the demand for power supply and reliability is increasing. In the power system, the reactor plays an important role as a key equipment. However, due to long-term operation, the reactor is affected by factors such as loss, aging and hidden faults, and its reliability gradually decreases. The operation state of the reactor is directly related to the operation effect of the power grid and the quality of the user’s electricity. Therefore, the application of reactor online monitoring and fault diagnosis in real life is very important. This paper considers the actual operation of the coastal power grid. Based on Qt software development platform, C + + language and MySQL database, an online monitoring and fault diagnosis platform for oil-immersed shunt reactors is developed. The application of the platform takes the online monitoring and fault diagnosis method of dissolved gas in oil as the core. The platform realizes the basic information management, online monitoring, fault diagnosis and suggestions for operation and maintenance of the reactor.

Evolution of mining-induced water inrush disaster from a hidden fault in coal seam floor based on a coupled stress–seepage–damage model

Water inrush originating from hidden faults in the coal seam floor is challenging to prevent due to their concealed nature. This paper develops a coupled stress–seepage–damage model for simulating rock fracture, implemented using the finite element method. The model is validated against compression-seepage tests on rock samples, capturing realistic dynamics of shear and tensile damage as well as permeability. The model is applied to the 27305 working face of a coal mine in Shandong Province, China, revealing the evolution of water inrush caused by a hidden fault. The results indicate that as the working face progresses, both the floor damage and the internal damage within the hidden fault escalate gradually. When mining reaches 80 m, the hidden fault has been activated internally, and the depth of floor damage reaches 13 m, which still has a certain distance from the hidden fault. At 100 m, the depth of the floor damage has stabilized, while the stress concentration at the hidden fault's tip increases, and it begins to expand if conditions for tensile damage are met. By the time mining reaches 110 m, the hidden fault has expanded 9.2 m in length and connected with the floor damage zone, forming a water inrush channel that links the aquifer to the working face, presenting a significant water inrush risk. This work provides an intuitive approach to understanding the evolution of water inrush from a hidden fault, aiding in the prevention of water inrush disasters in practical engineering applications.

Fault prediction of unmanned aerial vehicles based on entropy weight fusion and temporal graph convolutional network with non-Euclidian structure

Predicting weak and hidden faults in unmanned aerial vehicles (UAVs) is challenging due to their variable operation conditions and complex mechanisms. Conventional neural network models process the multisensory data in the form of Euclidean structure, the intrinsic connections among the individual data points are easy to be disregarded. Additionally, multisensory data are always directly fed into the model without adequately considering the importance or contribution of each sensor. Hence, an UAV fault prediction method is proposed by combining entropy weight fusion with a temporal graph convolutional network (GCN) to address the above problems. Firstly, the importance of multisensory data of UAVs are evaluated by each entropy value, and the multisensory data fusion is further realized by multiplying corresponding signal and entropy weight. Secondly, the multisensory data combined with fusion data are transferred together into graph-structure by adjacent matrix based on the node connection between different sensor data. Finally, the graph-structure data with non-Euclidian distance properties are input into temporal GCN to both capture the spatial and temporal relationship of the data, achieving better fault prediction results of UAVs. It is demonstrated that the proposed method is both applicable and superior in characterizing and predicting fault time series information of UAVs through parameter analysis and comparison studies with various existing algorithms.

Exhumation of the Cuonadong Sn–W–Be polymetallic deposit, Tethyan Himalaya: Implications for exploration

The Cuonadong Sn–W–Be polymetallic ore deposit is the first rare-metal deposit related to leucogranites with giant mineralization potential to be discovered in the Himalayan Orogen. However, the post-mineralization exhumation and preservation processes of this deposit have not yet been studied in detail, although these factors are key to the exploration and evaluation of rare-metal deposits in the Himalaya. Geophysical data have revealed that a hidden fault (i.e., the Jisong secondary fault) cuts the southern part of the Cuonadong ore deposit. In order to determine the effects of the Jisong secondary fault on the exhumation of the Cuonadong deposit, we undertook zircon and apatite (U–Th)/He dating, apatite fission-track dating, and forward and inverse thermal history modeling of the footwall and hanging wall of the Jisong secondary fault. Our results show that the Cuonadong deposit experienced two stages of rapid, post-mineralization exhumation at ca. 10–9 and ca. 5–4 Ma, separated by a period of differential exhumation at ca. 9–5 Ma. These exhumation events were likely caused successively by the arc-shaped Nading Fault, normal faulting on the Jisong secondary fault, and thrusting on the Main Himalayan Thrust, although climate-related erosion may have also had a role in the exhumation. Owing to normal displacement on the Jisong secondary fault, the Cuonadong ore deposit underwent differential exhumation of 300–700 m. This implies that the eastern part of the deposit is more favorable for exploration than its western part if the deposit has the same mineralization depth. This study demonstrates that low-temperature thermochronological methods can be useful in the exploration for rare-metal deposits in the Himalayan Orogen.

MultiURNet for 3D seismic fault attributes fusion detection combined with PCA

Identifying faults and fractures in complex block reservoirs is critical for recovering residual oil-gas. It has been found that improving the identification accuracy of neural networks and enhancing their ability to learn multiple fault features are key to accurately identifying complex faults, including low-order and hidden faults. In this study, we developed a U-shaped residual network (URNet) that intelligently identifies seismic faults using principal component analysis (PCA). Numerous synthetic seismic records were generated using convolution method. Multiple seismic attributes were generated based on amplitude attributes and preferred attribute bodies. PCA is used to pre-process the features of multi-attribute bodies, downscale and preserve the original data information and reduce data complexity and storage space. A residual block was added to the deep coding and decoding network structure to improve the expression capability of the neural network while preventing gradient vanishing. Naming the network structure as MultiURNet and the network model was applied to the generated data and actual data, and the identification of the high-order and low-order faults were both significantly improved with the clarity of the fault lines. The results confirm the feasibility and efficiency of the proposed method, which has significant potential for future exploration in shallow and medium-shallow oil and gas fields.

Fusion of Remote Sensing, Magnetometric, and Geological Data to Identify Polymetallic Mineral Potential Zones in Chakchak Region, Yazd, Iran

Exploration geologists are urged to develop new, robust, and low-cost approaches to identify high potential zones related to underground/unexplored mineral deposits because of increased depletion of ore deposits and high consumption of basic metal production industries. Fusing remote sensing, geophysical and geological data has great capability to provide a complete range of prerequisite data to accomplish this purpose. This investigation fuses remote sensing data, such as Sentinel-2 and Landsat 7, aerial magnetic geophysical data, and geological data for identifying polymetallic mineralization potential zones in the Chakchak region, Yazd province, Iran. Hydrothermal alteration mineral zones and surface and deep intrusive masses, hidden faults and lineaments, and lithological units were detected using remote sensing, aerial magnetic, and geological data, respectively. The exploratory/information layers were fused using fuzzy logic modeling and the multi-class index overlap method. Subsequently, mineral potential maps were generated for the study area. Some high potential zones of polymetallic mineralization were identified and verified through a detailed field campaign and drilling programs in the Chakchak region. In conclusion, the fusion of remote sensing, geophysical, and geological data using fuzzy logic modeling and the multi-class index overlap method is a robust, reliable, and low-cost approach for mining companies to explore the frontier areas with identical geologic conditions that are alleged to indicate polymetallic mineralization potential.

INVESTIGATION OF THE FREQUENCY OF PATIENT FALLS BY ROOT CAUSE ANALYSIS: KAYSERİ CITY HOSPITAL SAMPLE

Bu çalışmada hasta düşmelerinin sıklığını tespit ederek, yatarak tedavi edilirken düşen hastaların düşmelerine neden olan faktörleri belirleyerek kök neden analizinin yapılması amaçlanmıştır. Araştırmanın evrenini, Kayseri Şehir Hastanesinde 01/01/2019-31/12/2019 tarihleri arasında tüm kliniklerde meydana gelen hasta düşmeleri oluşturmuştur. Tanımlayıcı tipteki bu araştırmada örneklem seçimine gidilmemiş olup, örneklem yılı içerisinde kliniklerde yatarak tedavi görürken düşen 81 hastanın, düşmelerine dair bulgular değerlendirilerek, kök neden analizi yapılmıştır. Araştırmada veriler Düşme Olayı Bildirim Formu ile toplanmıştır. Elde edilen bulguların değerlendirilmesinde istatistiksel analiz için SPSS-22 paket programı kullanılmıştır. Tanımlayıcı analizler sunulurken; sayı ve yüzde dağılımları, aritmetik ortalama, standart sapma, medyan (ortanca), minimum-maximum değerler kullanılmıştır. Analiz ve yorumlama yapılırken ise PRISMA Yöntemi kullanılarak, EINDHOVEN Sınıflandırma Modelinden yararlanılmıştır. Kök neden analizi için; beş neden analizi yöntemi ile bir dizi şeklinde “neden” sorusu sorularak neden ağaçları yapılmıştır, toplamda 262 kök neden bulunmuştur. Her olay için 2-4 kök neden ortaya çıkmıştır. 81 düşen hastadan 28’i (%34,6) kadın, 53’ü (%65,4) erkektir, düşen hastaların yaş ortalaması 64 ± 17,6 (standart sapma:17,6), yaş ortancası 67 (min:3,5-max:93) olarak hesaplanmıştır. Klinik bazında en çok düşen hasta 21 (%25,9) hasta düşmesi ile fizik tedavi ve rehabilitasyon kliniğinde olmuştur. Düşen hastaların 78’i yüksek riskli iken 3 hasta düşük riskli olarak değerlendirilmiştir. Örneklem yılı içerisinde toplam 120.935 hasta yatışı olmuştur. Düşen hasta oranı bu dönem için hastane geneli 0,07 olarak hesaplanmıştır. Düşen hastaların 36’sının refakatçisinin olmadığı, 45’inin refakatçisinin olduğu halde 34’ünün düşme anında yalnız olduğu tespit edilmiştir. Düşme nedenlerinin kök neden analizinde 262 hatanın; 15’ini gizli hatalar, 4’ünü aktif-insani hatalar, 243’ünü de diğer hatalar olarak sınıflandırılması yapılmıştır.

Metallic-Mineral Prospecting Using Integrated Geophysical and Geochemical Techniques: A Case Study from the Bela Ophiolitic Complex, Baluchistan, Pakistan

An integrated geophysical and geochemical investigation was conducted to investigate the metallic minerals hosted in the mafic and ultramafic rocks in the Bela Ophiolitic Complex. Two thousand magnetic observations were made along with six vertical electrical soundings, with Induced Polarization (IP) targeting the anomalous magnetic zones. The magnetic raw field data were interpreted qualitatively and quantitatively, and two anomalous zones (A1 and A2) were identified on the magnetic maps. The residual magnetic values in the high-magnetic-anomalous zone (A2) ranged from 310 nT to 550 nT, while the magnetic signatures in the low-magnetic zone (A1) ranged from –190 nT to 50 nT. The high-anomalous zone (A2) was distinguished by a high IP value ranging from 3.5 mV/V to 15.1 mV/V and a low apparent and true resistivity signature of 50 ohm·m. Whereas, the low-anomalous zone (A1) was distinguished by very low IP values ranging from 0.78 mV/V to 4.1 mV/V and a very high apparent and true resistivity of 100 ohm·m. The Euler deconvolution was used to determine the depth of the promising zone, which for A1 and A2 was in the 100 m range. The statistical analysis was carried out using hierarchical classification to distinguish between background and anomalous data. The high-magnetic anomalous signature of probable mineralization was in the range of 46,181 nT–46,628 nT, with a total intensity range of 783 nT–1166 nT. The major and trace-element analysis of the 22 rock and stream sediments collected from the high-magnetic-anomalous zone confirmed the mineralization type. The geomagnetic and geophysical cross sections revealed that anomalous mineralization was concentrated with the anticlinal Bela Ophiolitic Complex. The generated results also aided in the identification of rock boundaries, depth, and hidden faults in the area. The findings revealed that the study area has excellent mineralization associated with the ultramafic-rock sequence.

Prospective Evaluation of Geothermal Resources in the Shangqiu Uplift of the Southern North China Basin with Magnetotelluric Detection

The magnetotelluric sounding (MT) method is used to detect and study the deep stratigraphic structure and hidden faults in the Shangqiu Uplift. A total of 4 MT profiles are arranged, and 97 stations are collected. The nonlinear conjugate gradient (NLCG) two-dimensional inversion method is used to jointly invert data from both the TE and TM modes after a dimensionality analysis and impedance tensor decomposition; reliable two-dimensional resistivity models are produced since the data quality is excellent. Three-dimensional inversion is carried out to full impedance tensor as well to produce a three-dimensional resistivity model of the study area, which shows good consistency with the two-dimensional models. The results show that the electrical structure of the Shangqiu Uplift has typical layered characteristics, which can be divided into three layers from top to bottom, namely low-, medium-to-high-, and high-resistivity layers. According to the resistivity models and in combination with the gravity, aeromagnetic, seismic, and regional geological data of the study area, a geological map of the basement rock of the Shangqiu Uplift is produced. Two prospective geothermal anomaly areas are proposed according to the distribution of the high-resistivity anomaly formed by the basement uplift, which has a good corresponding relationship with the high-value area of the regional geothermal field. A geothermal exploration well (SR-1) is constructed in one of the inferred prospective geothermal anomaly areas. The well is 1702 m deep, with a water output of 1500 m3/day and a wellhead water temperature of 51.5 °C. This is the geothermal well with the largest water yield in the Shangqiu area at present, which provides a new basis for future geothermal exploration, development, and utilization.

Concurrent 21. Presentation for: Ground surface monitoring for CO

Presented on Thursday 19 May: Session 21 Tracking the migration of injected CO2 is critical to understanding the performance of subsurface intervals selected for CO2 sequestration. Subsurface CO2 injection may cause a deformation at the surface of the earth. Measuring and analysing the shape and magnitude of this surface deformation provides confidence that sequestered CO2 will remain in the target formations and can alert operators to the existence of hidden faults or fractures which may necessitate redesign of the injection schedule or remediation of the geological hazards. Surface deformation information for onshore injection operations can be obtained via Interferometric Synthetic Aperture Radar (InSAR) satellite imagery or an array of high-precision tiltmeters installed in 10–15 m deep boreholes. However, in the case of offshore injection operations, InSAR data is not available. Due to the lack of tilt data at In Salah field at Krechba, Algeria, synthetic tilt data has been produced using a 3D forward model. The synthetic tilt time-series data at ten locations around each injection well has been used in inverse analysis. Results show that the shape and direction of the CO2 plume in the subsurface can be accurately determined through inverse analysis of the tilt time-series data. To access the presentation click the link on the right. To read the full paper click here

Ground surface monitoring for CO

Tracking the migration of injected CO2 is critical to understanding the performance of subsurface intervals selected for CO2 sequestration. Subsurface CO2 injection may cause a deformation at the surface of the earth. Measuring and analysing the shape and magnitude of this surface deformation provides confidence that sequestered CO2 will remain in the target formations and can alert operators to the existence of hidden faults or fractures which may necessitate redesign of the injection schedule or remediation of the geological hazards. Surface deformation information for onshore injection operations can be obtained via Interferometric Synthetic Aperture Radar (InSAR) satellite imagery or an array of high-precision tiltmeters installed in 10–15 m deep boreholes. However, in the case of offshore injection operations, InSAR data is not available. Due to the lack of tilt data at In Salah field at Krechba, Algeria, synthetic tilt data has been produced using a 3D forward model. The synthetic tilt time-series data at ten locations around each injection well has been used in inverse analysis. Results show that the shape and direction of the CO2 plume in the subsurface can be accurately determined through inverse analysis of the tilt time-series data.

Non-seismic geophysical analysis of potential geothermal resources in the Longgang Block, Northeast China

Although geothermal energy has many clear advantages, including its sustainability and environmentally friendly nature, research into potential geothermal resources across the Longgang Block, Northeast China, has been limited. Here we present the first analysis of the potential geothermal resources in this region that employs joint geological and non-seismic geophysical methods to identify target areas that may be economically viable. We acquire and analyze high-precision gravity, magnetic, and magnetotelluric sounding data, which are constrained using the petrophysical parameters of outcropping rocks across the Longgang Block, to conduct a comprehensive evaluation of the region’s deep geological structures and their geothermal resources potential, with a focus on identifying faults, rock masses, and thermal storage structures. We find that Archean granitic gneiss and Mesozoic rock masses in the deeper section of the Longgang Block possess weak gravity anomalies and high resistivities. We also identify thermal storage structures near these deeper geological units based on their extremely low resistivities. The data are used to infer the dip and depth of known or hidden faults, to constrain the spatial distribution of intrusive rock masses, and to determine the spatial distribution of subsurface thermal storage structures. The potential of the target areas for geothermal resources exploitation is divided into three grades based on contact depths between faults and thermal storage structures, and the scale of their thermal storage structures. Our results suggest that a joint non-seismic geophysical approach can be effective in locating and evaluating geothermal resources in complex geological settings.

Three-dimensional velocity structure around the focal area of the 2021 MS6.4 Yangbi earthquake

On May 21, 2021, an MS6.4 earthquake occurred in Yangbi, Yunnan province, China, which exhibited typical foreshock-mainshock-aftershock characteristics. To better understand the velocity structure of the focal area and adjacent fault zones, Pg/Sg travel times at 12 seismic stations for the local earthquakes with ML ≥ 1.5 from 2009–2019 and the Yangbi sequence in May of 2021 were used to invert the three-dimensional (3D) structures for both vP and vP/vS. The obtained structure extends deeply to 15 km for area (25°N–26.5°N, 99.5°E–101°E) at a horizontal resolution of 10× 10 km, and the accuracy of the vP velocity was verified using airgun signals excited by the Binchuan Airgun Transmitting Seismic Station (BATSS). The resulting vP and vP/vS images correlate with existing fault zones and the Yangbi sequence, including: (1) The shallow velocity structure at 0 km agrees with local topography, where the Binchuan basin exhibits low-vP and high-vP/vS values. From 3–15 km, vP and vP/vS show variations, and the boundaries are consistent with the main faults (e.g., the Weixi-Qiaohou-Weishan, Honghe, and Chenghai faults). (2) The largest foreshock (MS5.6), mainshock (MS6.4), and largest aftershock (MS5.2) occurred near the boundaries where both vP and vP/vS have clear contrasts. (3) Small earthquakes are also concentrated in the transition zone between high- and low-vP and vP/vS anomalies, and are biased toward low-vP/vS zones. (4) Boundaries in vP and vP/vS are observed at 20 km west of the Weixi-Qiaohou-Weishan fault, indicating that there may exist one hidden fault.

Effect of Crack Propagation on Mining-Induced Delayer Water Inrush Hazard of Hidden Fault

Hidden faults in deep coal seam floor threaten the exploitation of coal resources. Under the influence of mining and water confined in the floor, the cemented filler in the hidden fault will be eroded by water flow, in order to investigate the fracture characteristics and water inrush risk of hidden faults in floors above confined aquifer. Using the 27305 working face as geological background, the influence of the seepage scouring filler on the mechanism of water inrush from hidden faults was assessed by developing a stress-seepage coupling model and employing the finite difference method to simulate the seepage process of hidden faults under the combined action of high ground stress and high confined water. The evolution of seepage, shear stress, and plastic zone was also assessed. The influence of the hydraulic pressure of the aquifer and the thickness of a waterproof rock floor on the formation of the water inrush pathway was analyzed. Results indicate that (1) under the influence of mining, the hidden fault experienced the change process of stress stability, stress concentration, and stress release. The shear stress increases first and then decreases. The compressive stress decreases gradually due to stress release. (2) Water inrush disaster will not occur immediately when the working face is above the hidden fault. The delayed water inrush occurs in the mined-out area when the working face advances to 160 m, the floor failure zone is connected with the hidden fault failure zone, and the delayed water inrush channel is formed. (3) With the mining advances, the water pressure of aquifer is the same. The larger-angle fault leads to the thinner thickness of floor aquifer. The greater the influence of hidden fault on coal seam mining, the higher the danger of water inrush.

Geoinformational criteria for distinguishing the quasi-linear chains of earthquake migration in epicentral fields of complex geometry and variable density of shocks distribution

Within the framework of the basic model of migrating seismicity, the main geoinformation criteria for identifying quasi-linear chains of earthquakes in epicentral fields of complex geometry and variable density of shock distribution have been determined by numerical methods. The developed model is used to study the migrations of earthquake foci and identify zones of hidden seismically active faults: it provides statistical criteria for the presence of quasi-linear chains of seismicity migration
 and zones of hidden seismic faults in arrays of various volumes of seismological data as an excess at a given level of significance
 of the average numbers of chains of earthquakes, spatially temporal distribution of shocks. The established dependences of the average number of selected chains of random events on the sample size and site shape make it possible to reveal the presence of seismicity migration and zones of hidden faults under the given criteria of “significance”, “representativeness” and ISMA. The developed methods, implemented programs and patents lay the theoretical and practical basis for GIS technology for identifying hidden faults and studying the migrations of earthquake foci in the lithosphere of the Baikal rift system. Since the main laws governing the formation of the internal structure of continental fault zones and seismicity are determined by the fundamental properties of the progressive deformation of transgressive shearing realized within them and are uniform, the developed GIS technologies can be applied in other seismically active regions.

A Numerical Investigation of the Hazardous Injection Area of Induced Earthquake during Hydraulic Fracturing

Hot dry rock (HDR) geothermal energy has many advantages, such as being renewable, clean, widely distributed, and without time and weather limitations. Hydraulic fracturing is usually needed for the exploitation of HDR geothermal energy. It has many hidden faults in the reservoir/caprock sequences. Injecting fluid into underground formations during hydraulic fracturing often induces fault slip and leads to earthquakes. Therefore, to well understand the induced fault slip and earthquakes is important for the applications and development of HDR geothermal exploitation. In this study, we investigated the hazardous injection area of the induced earthquakes during hydraulic fracturing. The study was based on a hydraulic fracturing test in Qiabuqia geothermal field in China. According to the field, a fault-surrounding rock-fracturing region system was developed to study the influences of fluid injection on the stability of the specific fault. A total of 60 hydraulic fracturing regions and 180 numerical experiments were designed. The results revealed that the hazardous injection regions that threaten the fault’s stability were near to the fault and concentrated on the following four areas: (a) above the top of the fault in underlying strata; (b) above the top of the hanging wall of the fault in underlying strata; (c) near to the fault planes in both footwall and hanging wall; (d) at the bottom of the footwall of the fault in underlying strata. The hazardous injection area can be controlled effectively by adjusting the injection pressure.

Mapping of NW-Trending Hidden Faults in the Priamurye Region via Relief Analysis and Geophysical Fields

Mapping of NW-Trending Hidden Faults in the Priamurye Region via Relief Analysis and Geophysical Fields