Abbreviation (ISO4): Prog Geophy
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The present study investigates the interdecadal change in the interannual relationship between summer Sea Surface Temperature (SST) in the tropical Pacific and the Arctic Sea Ice Concentration (SIC) and its possible mechanism using 1979—2023 monthly SST and SIC data from Hadley Center and atmospheric reanalysis data from NCEP/NCAR. It is found that the relationship between tropical Pacific SST and SIC in Beaufort Sea experienced an obvious interdecadal change from an insignificant correlation to a significant positive correlation around the year 2001. The reason for the change is the strengthened SST anomaly in central tropical Pacific. During the period of 2001—2023, convective activity in central tropical Pacific intensified due to SST anomaly, enhancing Rossby wave propagating from tropic to high-latitude. Enhanced Rossby wave propagation which formed a zonal circulation pattern of "+-+-", creating favorable advection and radiation for SIC anomalies in Beaufort Sea. As a result, SIC in Beaufort Sea shows a significant positive correlation with SST in central tropical Pacific. Besides, we confirm that SST anomaly in central tropical Pacific can only unilaterally influence SIC in Beaufort Sea by using Liang-Kleeman information flow. Before the turning, due to weak SST anomaly in the central tropical Pacific, it is difficult to trigger a wave train reaching high latitudes, resulting in the correlation between SST in tropical Pacific and SIC in Beaufort Sea remain insignificant.
Technical methods related to the regional gravity fields, include precise geoid determination, downward continuation of gravity anomalies, and construction of regional models, which are greatly faced with challenges, such as low accuracy or efficiency, computation approximations, instability, and lack of criterion. This study introduces the fast implementation technique of ultra-high degree spherical harmonics analysis into the construction of regional gravity field, combined with satellite gravity field models of low to medium frequency spectrum and GNSS/leveling data. By employing a 5400-degree spherical harmonics analysis (SHA), it is possible to achieve a regional gravity field reconstruction with a resolution of 2 arc-minutes and an error less than 1 mGal for gravity anomalies, less than 1 cm for (quasi) geoid, and less than 0.4 arc-seconds for vertical deflection. Meanwhile, SHA can also be used for stable downward continuation of airborne gravity anomalies, which is verified to be more simple, accurate, and stable. Therefore, SHA is worth promoting and applying in the modeling of regional gravity fields and related data processing problems.
The correct classification of earthquake events is of great significance to regional seismic hazard assessment and the reduction of natural or artificial earthquake disasters. Over the years, many scientific and technological personnel have conducted a large amount of research on this topic. This article systematically summarizes the current mainstream understanding of the classification characteristics and difficulties of various types of natural and artificial earthquake events in China and abroad, as well as the application status of artificial intelligence in earthquake classification research. The results show that: (1) the classification of blasting earthquakes and tectonic earthquakes has made relatively rapid progress; (2) the identification and classification of volcanic earthquakes and landslide events generally face the problems of insufficient sample size and data imbalance in the dataset; (3) the recognition of induced earthquakes remains a difficult and controversial subject in classification research; (4) artificial intelligence methods, with their high accuracy, efficiency, and potential for future automation, have become the mainstream method for earthquake classification at present. Based on the current application status of artificial intelligence technology in earthquake classification, this paper discusses and proposes corresponding suggestions and development trends.
During the period of 18 to 22 April 2008, a visually slow drawdown in groundwater level signal with a magnitude of approximately 0.156 m lasting about 4.5 days was recorded in the Jingyang well, Shaanxi. The paper entitled "Pre-slip activities before Wenchuan MW7.9 earthquake at North China and Northeast Asia tectonic-block region" suggests that this episode originated from the pre-slip Xp2 phase of the tectonic block before the 2008 MW7.9 Wenchuan earthquake. However, the main signature of the "pre-slip Xp2 phase" is negatively correlated with the shape of low-frequency change of atmospheric pressure; therefore, we quantitatively investigated the pressure coefficient of the Jingyang well at low frequencies using the linear regression method. The final result indicated that the "pre-slip Xp2 phase" was mainly caused by a transient increase of atmospheric loading. This retrospective and reassessed study will help to reveal the real driving mechanism of the pre-slip Xp2 phase.
As a green, low-carbon, safe, high-quality and recyclable renewable energy, geothermal energy is of great significance to the adjustment of China's energy structure and the realization of the goal of "double carbon". As an environmentally friendly and non-destructive method, geophysical methods are widely used in the exploration of middle-deep geothermal resources, which can effectively detect deep hidden fault structures and obtain important information such as strata and buried depth. This paper systematically investigates the research and application status of common geophysical methods and exploration equipment at home and abroad in the detection of geothermal energy in medium and deep layers, analyzes the advantages of each geophysical detection method under its applicable conditions, and summarizes the research ideas of the detection of geothermal resources in medium and deep layers. According to the application examples of geophysical detection methods in geothermal areas, the adaptability, effectiveness and accuracy of geophysical detection methods in the detection of geothermal energy in medium and deep layers are expounded.
The geothermal doublet system which one well is designed for the extraction and the other is for recharge has been widely applied for geothermal extracting while in the dynamic evaluation for the hydrothermal geothermal resources. However, the neglect of the existence of the water flowing fracture can cause the inaccurate assessment for the geothermal resources in the thermal reservoir. In this study, combined the knowledge of the geology which mainly includes the rock stratum and geological structure, geothermics geology mainly including the temperature field and rock thermophysical parameters, and hydrogeology and based on the hydro-thermal coupling numerical simulation, the effect of water flowing fracture on the assessment of geothermal resources was studied detailedly by using the doublet well system, thus, the results of numerical simulation calculations will be more closer to the actual geological situation. This research mainly analyzed the temperature distribution characteristics within the thermal reservoir under the different extraction times, and the changing tendency of production temperature and the energy production rate of the production well from the thermal reservoir with time was also analyzed carefully under the conditions which the water flowing fracture was perpendicular or parallel to the plane (the plane was defined by the production and rejection wells), and after that the above simulation calculation results are compared with the case that no water flowing fracture was existed in the thermal reservoir. On the other hand, effect of different physical properties of the water flowing fracture mainly including the rock permeability, rock porosity and thickness of the fracture on the simulation calculation was also analyzed in this research. The results of this study can make the evaluation of geothermal resources more reflecting the actually geological conditions which is conducive for the subsequent development and utilization planning, and at the same time can provide a reference case for other study areas.
The Guide Basin, as a vital target area for the development of Hot-Dry Rock (HDR) in China, necessitates an assessment of its exploitation potential and an investigation into the feasibility of constructing Enhanced Geothermal Systems (EGS). Therefore, this study focuses on the HDR geothermal development in the Guide Basin. Firstly, the location of objective reservoir is determined and the geometry of EGS is designed. After that, a thermal-hydraulic-mechanical coupling model for HDR development is established. The heat extraction performance of water-based EGS and carbon dioxide-based EGS under different injection rate, injection temperature and well spacing is compared, and the most suitable working fluid for EGS in the Guide Basin is determined through comprehensive analysis. Subsequently, the non-dominated sorting genetic algorithm III is used to conduct a multi-objective optimization for the EGS engineering parameters (injection flow rate, injection temperature, and well spacing) in the Guide Basin and the technique for order preference by similarity to ideal solution (TOPSIS) is used to sort the individuals in the Pareto fronts. Then the optimal parameter combination recommendation is given and provide a guidance for the EGS construction. Finally, based on the optimal parameter combination, the development potential, economic and environmental benefits of geothermal resources in the Guide Basin are evaluated. The research results indicate: (1) Carbon dioxide is more suitable as the working fluid for EGS in the Guide Basin due to its more stability production and lower consumption; (2) The optimal combination of engineering parameters for EGS in the Guide Basin is 59.48 kg/s, 20.26 ℃, and 379.95 m; (3) The EGS in the Guide Basin can operate stably for 50 years with an average electric power of 2.28 MW and a production temperature over 168 ℃, yielding a total electricity output of 1014 GWh. The levelized cost of energy is only 0.052 ＄/kWh, with a reduction in greenhouse gas emissions ranging from 0.34 to 1.18 Mt during this process.
Landslides in the reservoir area are a key issue of national hydropower engineering safety and geological disaster prevention and control. During the water storage cycle, the water level in the reservoir area changes significantly, and water level fluctuations have a strong triggering effect on landslides in the reservoir area. This article takes the Baihetan hydropower station reservoir area as the research area, uses Small-Baseline Subset InSAR technology, combined with Sentinel-1 A data from the lifting rail, to monitor deformation in the early, middle, and late stages of water storage in the research area, and studies the impact of water level changes in the reservoir area on landslide deformation. The results showed that: (1) deformation monitoring was carried out in the study area using InSAR technology, and 11 unstable slopes were detected, with the maximum deformation reaching 0.14 m. Among them, 4 were known landslides, and deformation monitoring was carried out on typical landslides to study the impact of water level changes in the reservoir area on deformation; (2) Taking the cross mountain landslide and Qiaojia County landslide as examples, this study investigates the correlation between water level fluctuations and landslide deformation. Through Pearson correlation coefficient research, it is found that there is a strong correlation between significant changes in water level and landslide deformation rate. The correlation between the two is highest in the middle stage of water storage, and the impact of rising water level in the reservoir area on landslide deformation is greater than that of falling water level; (3) Taking a typical landslide as an example, a lag study was conducted on the water level and landslide deformation in the reservoir area through wavelet analysis. It was found that there is a lag period of about three to four months between the landslide deformation and water level fluctuations in the reservoir area.
Lithology identification is one of the key steps in the exploration and development of oil and gas resources. At present, using deep learning technology to identify lithology in logging can significantly improve the identification speed and accuracy. However, due to the shortage of data in logging data sets and the uneven distribution of lithology categories, the neural network is prone to overfitting in the training process, resulting in a decrease in the accuracy of the model. In order to solve these problems, a lithology identification model LogDiffusion based on diffusion probability model is proposed in this paper, which can generate high quality logging data and be used for training, so as to improve the classification accuracy of lithology identification. Based on the traditional diffusion probability model and considering the one-dimensional structure of log data, a fractional network FT-Unet for gradient estimation is designed in this paper, and an auxiliary classifier FT-Transformer is proposed to obtain accurate lithology labels. In addition, a threshold based dynamic labeling mechanism is proposed to improve the accuracy of the sampling algorithm. The experimental results on two small-sample blind well logging data sets show that this method can alleviate the problems of insufficient data quantity and uneven distribution of lithology categories in the logging data set to a certain extent, so as to improve the accuracy and precision of lithology identification.
The Chang6 reservoir of Ansai Oilfield in the eastern Ordos Basin is a representative example of a low-porosity and extra-low permeability reservoir, characterized by unfavorable physical properties and significant heterogeneity.Traditional reservoir modeling methods are difficult to effectively describe the heterogeneity changes between reservoirs in low-porosity and extra-low permeability reservoirs, which cannot meet the needs of precise oilfield development plan adjustment.Therefore, in order to meet the technical requirements of increasing oil production, the seismic reservoir modeling technology for low-porosity and extra-low permeability reservoirs is explored based on the development seismic of the first block in Ordos Basin.The multi-information seismic-constrained reservoir modeling is proposed.On the basis of combined well-seismic structural modeling and fracture modeling, combined with seismic attributes, the sedimentary microfacies model was constructed by deterministic modeling method based on the results of single-sand level sedimentary microfacies.Under the constraints of sedimentary microfacies model and spatial classification of seismic lithology probability body, a high-precision lithofacies model is established by using sequential Gaussian simulation method.Based on the lithofacies model, the seismic porosity inversion body is usedto further constrain the spatial classification and establish the porosity model.The permeability model is calculated by the empirical formula of pore-permeability relationship, and the oil saturation model is established by Kriging interpolation method. The results show that the seismic constrained reservoir model exhibits evident features of evolving reservoir physical properties, well-defined reservoir boundaries, and clear interlayer configuration relationships.The reliability of the reservoir model established through this technology is further substantiated by analyzing production dynamic data, enabling precise characterization of multi-stage thin sand-body reservoir groups.The technology takes advantage of abundant information of lateral changes of development seismic, solves the problem of inter-well uncertainty of traditional stochastic simulation modeling method, and realizes fine characterization of physical property distribution law of significant heterogeneous reservoirs.The seismic constrained reservoir model has been applied to perfect the corresponding relationship between injection and production and reservoir edge expansion.It provides effective technical support for the stable production of Ansai oilfield and promotes the application of development seismic in Ordos Basin.
Deep learning applied to seismic First Break (FB) picking has been developed for many years, and numerous researchers have used Image Semantic Segmentation Networks (ISSNs) for multi-channel FB picking. The existing seismic FB picking method based on ISSNs usually adopts two label calibration and FB determination methods, one is to divide the seismic signal into pre-FB and post-FB, and pick up the FB through mask segmentation; the other is to divide the seismic signal into FB and non-FB, and pick up the FB by extracting the highest confidence point of each trace. The former suffers from FB false pickup with localized regional continuity due to the mask edge blurring problem; The latter, because of the large proportion of positive and negative samples, tends to make the network hard fitting and cannot be applied to data with complex FB waveforms and large size. Based on this, a dual-channel mask interaction seismic FBs picking method is proposed, which ensures the network's FBs feature recognition ability by banded FBs range mask, and enhances the network's FBs accurate picking ability by linear preferred FBs mask, which effectively avoids the shortcomings of the existing methods. Theoretical experiments show that the method has good noise resistance and can be generalized to higher noise level data by training in low noise level data. When the method is applied to the field data, it achieves higher FB picking accuracy than the existing methods, and the number of traces with picking error of 0 ms is as high as 75.9%, which is 7.1%, 26.8%, and 15.6% higher than that of STUNet, SegNet, and Res-Unet, respectively, and greatly improves the efficiency of high-quality seismic FB picking. Meanwhile, the approach adopts a lightweight network model with high inference efficiency and easy engineering deployment, which has practical application value.
In the process of reservoir drilling and development, it is of great significance to accurately extract, identify and evaluate the fractures in the formation to guide the drilling and development of oil and gas exploration. To solve the problem of imprecise fracture region segmentation by traditional methods, a fracture segmentation method based on Formation Micro-Scanner Image based on deep learning is proposed. Firstly, F-Criminisi algorithm is used to repair the blank strip with missing pixel information in the original FMI logging image. Then, a generative adversus-network based on U-Net is constructed, and dual attention mechanism is introduced to construct a fracture segmentation model to achieve accurate fracture segmentation under complex background. Combining pixel and edge information, loss function is designed to enable the model to more accurately segment the fracture and background region in the logging image and make the fracture boundary in the segmentation result clearer. In this paper, the proposed model is tested by using real FMI logging image of carbonate reservoir. The results show that the Dice coefficient of the proposed fracture segmentation method is 5% higher than that of the classical fracture segmentation model U-Net. This method can accurately extract fracture information from FMI logging images, and provides a basis for subsequent quantitative calculation of fracture parameters and logging interpretation, and has good practicability.
Full Waveform Inversion (FWI) is an important method to obtain high-resolution velocity models. However, the seismic data are absence of low-frequency components, the conventional FWI results will have serious cycle skipping problem, which affects the accuracy of the final velocity modeling. For this reason, this paper proposes a local-scale frequency-wavenumber domain phase inversion method, which fully considers the local features of seismic data in the time and offset directions, and utilizes the local-scale decomposition strategy of seismic data and 2D Fourier transform to construct a local-scale frequency-wavenumber domain phase misfit function, to recover the low-wavenumber components of the velocity model and to provide a better initial velocity model for the FWI method. In this paper, we first utilize a 2D sliding window function to extract the local-scale seismic data, and combine it with the 2D Fourier transform to establish the local-scale frequency-wavenumber domain phase information based misfit function. Then, we derived the adjoint-source and gradient operator corresponding to the phase inversion in the local-scale frequency-wavenumber domain. Finally, the test results of the Marmousi model and the igneous-carbonate model show that the local-scale frequency-wavenumber domain phase inversion can provide a better initial velocity model for the conventional FWI method and mitigate the FWI cycle skipping.
The integration of geological engineering is one of the key technologies for efficient development of tight oil, and plays a very important role in the development of tight oil in Chang 8 member of the lower Yanchang Formation in West Ganquan. However, the evaluation criteria for geological and engineering sweet spots have not yet been formed in this block, which restricts the deployment of future oil and gas exploration and development plans. Therefore, using logging data to identify reservoirs in Chang 8 member of the study area, the evaluation index system of geological sweet spot is formed in terms of source rock, diagenetic facies and reservoir distribution characteristics. From brittleness index, rock stress and strain test, rock tensile fracture test, the evaluation index of engineering sweet area is established. The results show that: (1) The identification accuracy of reservoir fluid properties of Chang 8 member in the study area can reach 90% by differential analysis and fluid sensitive parameter method; (2) An evaluation index of geological sweet spot area of tight oil reservoir is established based on sand thickness, reservoir thickness, sedimentary facies, porosity, diagenetic facies and TOC*H parameters; (3) On the basis of petrophysical experiments and actual construction results, the evaluation indexes of the sweet spot of Chang 8 tight reservoir engineering in the study area are established from the aspects of petrophysical parameters and the optimization of differentiated fine-cut volumetric fracturing process. Under the constraint of geological sweet spot and engineering sweet spot, the recovery rate of Class Ⅰ reservoir can be increased from 5.3% to 17.3%, Class Ⅱ reservoir can only be increased from 4.86% to 8.19%, and Class Ⅲ reservoir can only be increased from 2.81% to 4.95% by optimizing fracturing process parameters.
In order to clarify the Nuclear Magnetic Resonance(NMR) characteristics and influencing factors of gas-water layer of He8 member in southeast Sulige of Ordos Basin, two-dimensional NMR technology was used to characterize the gas-water layer characteristics, combined with the analysis results of formation water, reservoir physical properties, formation anisotropy and gas supply, the NMR response characteristics of the gas-water layer of He8 member in the study area were clarified. The relationship between formation water, pore type, pore throat structure, formation anisotropy, gas supply and reservoir gas bearing is analyzed. The results show that: ①The formation water in the study area is mainly CaCl2 type, but the salinity difference is strong, and the distribution is 3669~325000 mg/L. The water type is all CaCl2, the pH value is 4.21~8.98, and it is weakly acidic.[r(Na+)/r(Cl-)] was less than 0.61, the coefficient of chloride to magnesium[r(Cl-)/r(Mg2+)] was greater than 7.0, and the coefficient of magnesium to calcium[r(Mg2+)/r(Both Ca2+)] are less than 0.69, and the metamorphic coefficients[r(Cl--Na+)/r(Mg2+)] are more than 0.47, indicating that the formation water is in a relatively stagnant reduction state, the formation is strongly sealed, and the natural gas is well preserved. ②The distribution of gas-water layers in He8 member in the study area is complex, and two-dimensional nuclear magnetic resonance technology can effectively distinguish the gas-water layers. ③The pore types of the reservoir in He8 member are mainly residual intergranular pores and feldspar solution pores, with porosity ranging from 2.70% to 14.48% and permeability ranging from 0.04 to 15.92×10-3 μm2. The reservoir physical properties affect the gas bearing properties of the reservoir, and the porosity and permeability of the reservoir are greater than 7.0% and 0.2×10-3 μm2, respectively. The porosity and permeability of the gas-bearing and differential gas layers are 5%~9.5% and (0.02~0.7)×10-3 μm2, respectively, while the porosity and permeability of the dry layer are less than 5% and 0.1×10-3 μm2, respectively. The anisotropy of the gas layer is between 15%~20%, and that of the dry layer is less than 6%.
The electromagnetic wave resistivity logging tool for Logging While Drilling(LWD) is one of the most widely used logging tools in horizontal well development. However, the anisotropy of the formation and the distance between the surrounding rock and the boundary in the horizontal well environment can cause distortion in the electromagnetic wave resistivity measurement values, leading to the common problem of low drilling rate in the development of thin reservoirs. In this paper, taking the electromagnetic wave LWD resistivity tool of CNLC as an example, the numerical simulation method is used to investigate the instrument response law in the horizontal well formation, and the characteristic signals indicating the boundary distance and anisotropy of the formation are defined and quantified, and the combination of characteristic signals and classification inversion is used to realize the quantitative calculation of the anisotropy and multiple boundary distances of the conventional electromagnetic wave LWD resistivity tool in complex formations. The boundary distance, horizontal resistivity and vertical resistivity calculated by inversion are consistent with the changes in borehole trajectory, the response characteristics of logging curves and the formation occurrence information displayed by borehole imaging, which verifies the rationality of the method. This method is suitable for obtaining boundary distance, anisotropy and formation resistivity parameters from conventional LWD instruments, quantifies the boundary detection ability of conventional electromagnetic wave resistivity instruments, provides a new idea for precise geological guidance of thin-bedded and complex oil and gas reservoirs, and provides a technical method for the fine evaluation of post-drilling formations, and has great potential application value.
Influenced by the style of strike-slip fracture and the coupling relationship of fracture-reservoir-collection, the carbonate ultra-deep fracture-controlled reservoirs have strong non-homogeneity in the same zone, and the planar variability of different zones is large. The drilling wells reveal that the fracture-controlled reservoirs are mainly dominated by caves and cracks. The fracture-controlled scale reservoirs are mainly developed in the strong energy anomaly zone near the fracture plane. Therefore, based on the analysis of the difference in seismic response of fractures such as pulling section, translational section, and extrusion section, and the advantageous attribute preference of the drilled wells, we conclude the comprehensive attribute portrayal techniques for different types of ultra-deep fracture-controlled reservoirs in the Shunbei area. Pull segment optimization significantly improves coherence properties. Coherent energy gradient properties are preferably utilized in the translation and extrusion sections. The impedance properties of internal cavernous reservoirs are meticulously analyzed through the employment of phase-controlled inversion. In turn, the drilling trajectory is guided according to the differences in fracture characteristics, specifically: the width of fracture zones in the pulling section and extrusion section is large, and the reservoirs are mostly pore-type, so it is recommended to design horizontal wells, while the translational section is dominated by fractured reservoirs, so it is mostly recommended to design small-angle well trajectories. Overall, this study is based on the fine delineation of the spatial distribution law of ultra-deep fracture-controlled reservoirs, the use of drilled wells, the preferred seismic attributes, and according to the characteristics of the fracture itself, a comprehensive guide to predicting the drilling trajectories.
With the further evolution of oil and gas exploration and development technology, the traditional artificial fault interpretation has some defects such as strong subjectivity, heavy workload and low efficiency, which cannot meet the needs of efficient identification of faults on seismic data and the exact realization of structural characteristics in the study area interpretation needs. This article explores the process, advantages, application scope, and limitations of various representative fault identification technologies found on a large number of domestic and foreign literature. Based on this, it can be roughly divided into three categories of fault identification technologies represented by single seismic attribute, multi attribute fusion, and artificial intelligence. Single attribute fault interpretation techniques mainly include spectral decomposition, coherence volume, variance volume, etc. These techniques and methods are mainly applied in the early stage of seismic exploration, and are relatively effective for the identification of large faults. In terms of small fault recognition, the seismic multi-attribute fusion technology based on RBG attribute fusion has unique advantages. By changing the weight of different attributes, the structural information of the fault is highlighted, so as to reduce the interference and reduce interference and ambiguity. With the advent of the big data era, fault identification technology based on artificial intelligence has been widely used. Ant body tracking belongs to the early artificial intelligence fault identification technology, which partly improves the accuracy of fault identification, but there are still some problems such as strong multi-solution and low anti-noise ability. Since then, neural networks have been introduced into seismic data processing and interpretation, mainly including image classification and semantic segmentation. In particular, residual neural networks, convolutional neural networks, fully convolutional neural networks and U-Net have been widely used in the research of fault recognition, which promote further development of automation and intelligence in fault recognition. This paper summarizes and compares various fault identification techniques, proposes future development directions, techniques, proposes future development directions, which provides new solutions for the use of seismic data for fault interpretation and identification in oil and gas exploration for further.
The seismic inversion method based on rock physics constraints aims to deal with the challenge of accurately predicting physical properties of complex tight sandstone reservoirs, which often exhibit strong ambiguity. This ambiguity makes it difficult to characterize the reservoir and accurately select high-quality ones. By employing theoretical rock physics modeling and a Bayesian probability inversion framework, along with pre-stack seismic data and well logging data, a method is proposed to predict the physical properties of complex tight sandstone reservoirs through seismic analysis. This approach allows for a detailed characterization of these reservoirs and provides technical support for exploring such complex formations. Because complex tight sandstone reservoirs typically have low porosity, low permeability, and intricate pore structures, assuming a uniform pore structure makes traditional rock physics modeling and reservoir parameter seismic inversion methods inadequate. Hence, this paper derives seismic reflection coefficient equations for complex tight sandstone reservoirs, considering parameters like porosity, water saturation, and pore aspect ratio. Using these equations, a Bayesian pre-stack seismic inversion method is developed, which directly estimates the physical parameters and pore geometry of complex tight sandstone reservoirs using Bayesian linear theory. Results indicate that this method not only provides more accurate predictions of rock physics parameters but also yields physical property estimates that align better with actual wellbore measurements. This demonstrates the method's effectiveness and precision in predicting physical properties of complex tight sandstone reservoirs using seismic data.
The igneous rocks in Laizhou Bay, Southern Bohai Sea, exhibited complex and variable lithologies, posing significant challenges to accurately identify lithology using conventional logging cross-plots. To improve the precision of igneous rock lithology identification in study block A, a high-efficiency Light Gradient Boosting Machine (LightGBM) model was employed to identify lithology. Furthermore, the utilization of a greater number of hyperparameters by LightGBM necessitated the employment of the Whale Optimization Algorithm (WOA), which was renowned for its robust global optimization capabilities, to identify the optimal parameter solution. Consequently, a logging lithology identification approach was proposed based on WOA-LightGBM. Firstly, logging response of lithology was analyzed, and logging data with complete geological information, such as core and thin section, and complete regular nine logging curves were selected as the sample set. The sample set is then input into six models, namely, WOA-LightGBM, WOA-AdaBoost, WOA-SVM, LightGBM, AdaBoost, and SVM, for identification. And the results of identification process were compared and verified. Finally, the recognition models were applied to 15 wells. The results demonstrated that WOA-LightGBM model with optimal hyperparameters exhibited the highest recognition accuracy and the most robust generalization ability when the whale population was 50. There cognition accuracy in the sample set reached 91.62%, and macro-average F1-score was 87.41%, ROC-AUC was 0.9676, PR-AUC was 0.8726, Matthews Correlation Coefficient was 0.8902, and 0.3401 for Cross-entropy Loss. Thus, the WOA-LightGBM method can be employed as an effective means of intelligently recognizing the lithology of the igneous rocks in the Bohai Sea by utilizing logging curves. This approach can also serve as a reference for igneous lithology identification in other similar blocks.
The high temperature and high pressure environment will cause significant changes in the Nuclear Magnetic Resonance(NMR) relaxation spectrum, which makes the methods and models based on the normal temperature and pressure state ineffective in the actual formation evaluation. In order to study the effect of temperature on the NMR response of porous media, eight types of artificial sandstone cores with different permeability, porosity, and shale content were manufactured, and NMR temperature-pressure experiments were conducted with 100% water saturation, oil saturation, and saturated oil-water two-phase conditions, respectively. The comparison of the NMR relaxation spectrum shapes measured under different temperature-pressure conditions indicates that pressure has little effect on the NMR response of porous media, while the effect of temperature on relaxation time is related to the wettability of the porous media, and the short relaxation peak is much less affected by temperature than the long relaxation peak. By statistically summarizing the variation patterns of core NMR porosity measured under different conditions, a temperature correction formula for NMR porosity was derived, and the porosity correction model under saturated oil and water state is determined.
In recent years, the production of tight sandstone gas in China has been rising, how to analyze the internal "sweet spot" of tight sandstone reservoir based on the characteristics of low porosity and low permeability has become a key issue. In this paper, the petrophysical model of tight sandstone is established by analyzing the petrophysical characteristics of tight sandstone and aggregating the pore structure connectivity of tight sandstone. Then, combined with the characteristics of the actual work area, the geophysical "sweet spot" are divided according to the porosity, P-wave impedance and other parameters. The sensitive parameters of "sweet spot" of tight sandstone reservoir, such as the ratio of bulk modulus to shear modulus(K/μ) and the ratio of P-wave velocity to S-wave velocity, are obtained, which lay a foundation for subsequent pre-stack seismic inversion for "sweet spot". Finally, the reflection coefficient equation applicable to the sensitive parameters of tight sandstone "sweet spot" is derived based on the elastic impedance inversion, and the quantitative prediction of class Ⅰ sweet spot to class Ⅱ sweet spot (coarse-grained rock facies) is realized according to the P-wave modulus and the sensitive parameters of "sweet spot", which effectively indicates the gas-bearing reservoir area and provides a reference for the evaluation and development of low permeability tight sandstone reservoir.
Triaxial compression tests of terrestrial reservoir rocks were carried out with the reservoir rocks of the Lianggaoshan Formation in the eastern Sichuan Basin as the research object. The mechanical properties, damage modes, and energy evolution laws of sandstone and shale were investigated, while the morphological characteristics of the distribution of cracks in the reservoir rocks were determined based on the fractal theory. The results show that the average values of sandstone and shale compressive strength are 293.74 MPa and 140.48 MPa respectively in the range of the studied depth. Sandstone has strong hard and brittle characteristics, showing cross-shear expansion damage mode; shale damage mode is splitting damage. The fracture distribution pattern after rock damage possesses statistical self-similarity. The shale fractal dimension is large, the complexity of the fracture network is high, and the factorability is good. In addition, the energy is mainly dissipated by energy storage and internal crack extension before the ultimate elastic energy, and the instantaneous release of stress-driven elastic energy produces macroscopic damage after the ultimate elastic energy. The results of the study can provide an understanding and theoretical reference for the development of reservoirs in terms of mechanical properties and energy evolution.
Seismic samples are typically designed on a perfect Cartesian grid. However, field constructions can disrupt the sampling geometry, resulting in the samples missing or off-the-grid. Our research goals are to simultaneously regularize off-the-grid samples and interpolate missing data for 3D seismic data under the framework of compressive sensing, which combines a 3D curvelet transform, a fast iterative threshold algorithm, and a merging sampling operator. The new sampling operator combines a binary mask with a barycentric Lagrangian operator for simultaneous interpolation and regularization. The fast iterative threshold algorithm is helpful to improve the interpolation accuracy and efficiency while solving the ill-posed problem. Finally, we demonstrate the effectiveness of the proposed approach by simulated and field datasets.
The carbonate reservoir of X structure in PuGuang gas field of Sichuan Basin has great potential for gas development and gas-bearing prediction technology plays a key role in the rolling development of the area. The lithology in the area is relatively stable but local feature of porosity changes rapidly. The gas-bearing indicators constructed by conventional methods are affected by changing porosity, resulting in insufficient indicating ability and poor consistency between prediction results and drilled wells. Through rock physics modeling and fluid substitute analysis, fluid indicator mixing between gas- and water-bearing reservoir is clarified; Combining the relevance between porosity and P- and S-wave impedance, a gas-bearing indicator construction method considering the influence of porosity was proposed. Based on prestack inversion and porosity inversion method, a gas prediction workflow of the study area is established and accurate prediction of gas-bearing reservoirs is achieved. The application results indicate that porosity-involved fluid factor can effectively suppress the influence of porosity during gas-bearing prediction, improve the prediction accuracy of gas-bearing reservoirs, and efficiently support exploration and development of the study area.
The Chang 8 tight sandstone reservoir is taken as the research object, and combining with the refined classification method of fluid distribution pore based on NMR fractal theory, the fluid motility of three different types of tight sandstone core samples were carried out to quantitatively characterize the fluid motility with the NMR tests. The experimental results show that the fluid motility of different types of cores is the result of the coupling of physical properties, lithological characteristics and microscopic pore inhomogeneity, and the fluid motility of larger pore sizes in cores significantly affects the fluid motility of cores; the fluid motility of different types of cores mainly occurs in P1-2 and P1-3 pores, and the amounts of these two types of pores and the amounts of their movable fluids determine the fluid motility of cores The pore structure coefficient and fluid motility coefficient have certain advantages in quantitative characterization of fluid motility, and the complexity of pore structure and fluid motility of P1-2 and P1-3 pores ultimately determine the fluid motility of cores.
Transient electromagnetic wave logging is one of the important methods for subsurface media detection, especially suitable for detecting anomalies near wells. However, the electromagnetic response of wellbore anomalies is diverse and complex, demanding a precise positioning and quantitative characterization method. This method needs to accurately identify key attributes of the anomalies, such as their position, shape, size, and electrical properties, and provide quantitative descriptions. In this study, the three-dimensional Finite Difference Time Domain(FDTD)method in the time domain is employed to investigate the transient electromagnetic field responses of homogeneous formations, horizontally layered anomalies, and three-dimensional block anomalies. Factors such as anomaly resistivity and position are examined to understand their influence on the measurement responses. By analyzing the responses generated by scattering bodies, important information regarding the extension of layered media and the position, size, and response magnitude of three-dimensional isolated anomalies is revealed. A layered wellbore anomaly electrical profile inversion technique is proposed based on the full-area apparent resistivity inversion method. To address the issue of late signals in the full-area apparent resistivity inversion method that cannot accurately reflect the true variation of formation resistivity, a direct vertical partition inversion combining gradient optimization algorithm is proposed. Additionally, a smoke ring inversion algorithm is employed for three-dimensional block anomaly electrical profile inversion. The improved detection method achieves quantitative characterization of wellbore anomalies, significantly improving the accuracy of positioning and electrical property extraction of isolated anomalies near wells, with an overall characterization error of less than 5%. This improved detection method is of great significance for petroleum and solid mineral exploration, aiding in determining the distribution and reserves of oil, gas, and solid mineral resources. It can guide decision-making in exploration activities and optimize resource development plans, thereby enhancing the accuracy and reliability of wellbore anomaly detection. Simultaneously, accurate detection of underground anomalies contributes to understanding the characteristics of subsurface structures, guiding engineering design and construction, and improving the efficiency and safety of engineering projects.
Supercritical geothermal can extract more than ten times the energy of conventional Enhanced Geothermal System (EGS), and become the development direction of new energy. Although China has become the country with the largest direct utilization of medium and low temperature geothermal resources, the level of exploration and development of deep underground high temperature geothermal resources needs to be improved. In this paper, we analyze the research progress of high temperature and high pressure physics experiment, numerical simulation, geophysical exploration and monitoring methods for supercritical geothermal, and the rock-fluid-gas geophysical properties of three-phase medium are summarized and analysis. And we give the typical high temperature geothermal area in China for supercritical geothermal resource exploration potential evaluation preliminary discussions, The potential exploration areas of deep supercritical geothermal resources based on geophysical survey results are predicted to provide support for the commercial utilization of supercritical geothermal resources in China.
The portable frequency domain electromagnetic detection instrument has been widely used in the field of urban near-surface exploration because of its high sensitivity, strong anti-interference ability, simple operation and high measurement efficiency. Due to the smaller scale of urban geological exploration targets, three-dimensional inversion is more advantageous than one-dimensional or two-dimensional inversion in terms of data interpretation accuracy. In order to study the effectiveness of the portable frequency domain electromagnetic detection instrument in urban shallow surface exploration and the superiority of 3D inversion, this paper conducts 3D inversion of GEM-2 measured data from a test site in Shanghai, and compares the results with the traditional 1D inversion results. The excavation results show the correctness of the 3D inversion algorithm proposed in this paper and the feasibility and superiority of its application in urban underground space detection.
Ground Penetrating Radar (GPR) is widely used in the fine detection of shallow structures such as urban road disease detection and archaeology, etc. Small-scale underground geological bodies such as cavities and cracks are usually the most concerned detection objects. In general, the energy of hyperbolic diffracted waves generated by small-scale underground geological bodies in the measured GPR profile is weaker than the linear reflected waves generated by the subsurface layered interface, and is easily mixed or masked by the reflected waves with stronger energy, which seriously interferes with the accurate identification and interpretation of small-scale targets. To this end, this paper proposes a multiple singular spectrum analysis method based on k-means clustering algorithm to separate the reflected and diffracted waves in the GPR profile. Then, the k-means clustering algorithm is used to cluster the all singular spectrum, and the singular values in the singular spectrum are divided into k classes according to the similarity, and the several types of singular values representing the reflected wave and the noise are set to zero, and some of the singular values representing the diffracted wave are retained to reconstruct the GPR diffraction wave field. Numerical experiments show that the multiple singular spectrum analysis method based on k-means clustering algorithm can efficiently separate the reflected wave from the diffracted wave. Compared with the reverse time migration of the unseparated GPR data, the imaging resolution of the small-scale geological body is higher and easier to be identified in the separated diffraction wave reverse time migration, which provides a feasible and effective method for the high-precision interpretation of small-scale targets.
For Bohai metamorphic buried hill, with the characteristics of rapid vertical and horizontal velocity change and strong reservoir heterogeneity, the prediction of fracture reservoir plays a crucial role in the oilfield development. Conventional fracture prediction methods are difficult to accurately predict the buried hill fracture reservoir. A new pre-stack inversion method for high-angle fracture reservoir is proposed in this paper. The method firstly carries out texture analysis based on gray level co-occurrence matrix on the original seismic data, extracts the seismic high-angle reflection information reflecting the response of the fracture reservoir, and integrates it with the low-frequency model of conventional pre-stack inversion to construct a low-frequency model suitable for the strong heterogeneous reservoir in the buried hill of the Archean space, and then carries out fine pre-stack inversion. In this paper, the method is applied to the prediction of fracture reservoir in Bozhong 26-6 oilfield. The results show that the method can improve the inversion effect and the prediction accuracy of fractured reservoir in Bozhong 26-6 oilfield, and provide a reliable basis for the deployment of development wells in Bozhong 26-6 oilfield.
As an important component of Transient Electromagnetic (TEM) prospecting, the performance of a TEM transmitter almost determines the effectiveness of this prospecting method. In order to accurately prospect shallow and even very shallow layers using multi-turn small coils, this paper designs an improved TEM transmitter based on SiC MOSFET. SiC MOSFET is a third-generation semiconductor that offers significant improvements in voltage withstanding, current withstanding, heat dissipation, and response speed compared to widely used Si IGBT. The shut-off time, as a critical parameter of the transmitter, essentially determines the degree of coupling between the primary and secondary field signals. To prevent losing information in even very shallow and relatively shallow layers, the transmitter designed in this paper supports switching transmission between large and small currents. When prospecting in even very shallow or relatively shallow layers, a small current of 1.1 A can be selected, with a shut-off time of only 4 μs. When prospecting in shallow layers, a large current of 16.2 A can be selected, with a shut-off time of 35 μs. To provide transmitting current data use for post-processing, this paper designs a current acquisition system that supports dynamic sampling rate to collect the current waveform in the whole time. When the current waveform is in the rising or falling edge area, the acquisition system automatically selects a high sampling rate of 1.8 MSPS for sampling. When the current waveform is in the steady-state area, the acquisition system automatically selects the lowest sampling rate of 50 KSPS for sampling. Tests show that by sampling with dynamic sampling rate, the acquisition accuracy and data volume can be effectively balanced, thereby ensuring the stability of the storage system. In addition, the transmitter board has a small size of only 255 mm×192 mm, and supports 12 V battery power supply, so it has good portability and can improve field prospecting efficiency to a certain extent.
Forensic military geophysics is a new branch of military geophysics in the field of military intelligence reconnaissance and identification with high-resolution measurements of the shallow underground layers of geophysical methods on typical military scenes including of the medium and small-scale battlefield spaces of tactics and combat military activities, which is used to directly verify the geological structure information of the reachable area, so as to infer the geophysical characteristics of the detection targets in the unreachable area by a close analogy of similarity in geological environment, and to solve the problem of effective reconnaissance and identification of geological intelligence evidence in the unfamiliar battlefield environment. A series of geophysical methods mainly include electrical methods, electromagnetic methods, seismic exploration and magnetic methods, which are applied to military scenes of the known battlefield environmental survey and the unknown battlefield intelligence reconnaissance. The key of the application to forensic military geophysical methods is similarity, contrast, rapidity, and non-destructive testing, which extremely could be in accordance with reconnaissance and identification to the physical characteristics of hidden objects as evidence constraints of battlefield environmental intelligence. The three types of typical examples consisting of projectile contact explosion damage effect in battlefield reconnaissance, military vehicle maneuverability in trace identification, and hidden target search underwater indicated that the resistivity method, R-wave survey and Ground Penetrating Radar (GPR) have a good identification effect on the remains evidence from military activities in shallow subsurface. This paper proposes that the multi-method application of forensic military geophysics is suitable to investigate and take the evidence for subsurface geological information of battlefield dynamic change conditions. The combination of geological and geophysical methods can effectively enhance the evidence identification effect. A multifaceted approach to the study of forensic geophysics and military geology will promote the theoretical innovation and practical application of military geophysics.
The Bozhong 19-2 structure is located in the southwest of Bozhong Depression, with favorable accumulation background. The shallow layer has undergone multiple rounds of exploration, but no large-scale discovery has been made. The main target layer of the lower Ming section is deposited by the meandering river, and the longitudinal and transverse direction of the river changes rapidly, and the contact relationship of the sand body is unusually complex, which presents a weak seismic reflection artifact locally, which does not conform to the objective spreading rule of the sand body and affects the description of the continuous sand body. Through forward analysis, it can be seen that the seismic weak reflection phenomenon is mainly affected by the comprehensive factors such as the absorption and attenuation of the stratum, the thickness of the target layer, the physical properties of the target layer, the velocity of the overlying stratum, the structure of the overlying stratum and the distance between the target layer and the overlying stratum. The amplitude of the original seismic data is weakened and the frequency band is narrowed. In this paper, the compressed sensing optimization reconstruction algorithm is used to reconstruct the original signal, and the reconstructed signal is divided into high frequency body and low frequency body. Then the original signal is used as the input of the intermediate frequency body to realize the attribute fusion, and finally the fusion data body is obtained. The main frequency of the data body is improved, the frequency band is broadened, and the recovery of seismic weak reflection is realized. This method can make the recovery results more in line with the real underground situation without relying on logging data, so as to more objectively reflect the distribution law of shallow sand bodies, which is conducive to the characterization of shallow lithologic traps.
The soil and groundwater pollution caused by gas station leakage is one of the main types of urban underground pollution. The soil and groundwater pollution caused by gas station leaks is one of the main types of urban underground pollution. In order to achieve this goal, we design a new acquisition method of three-dimensional inter-well resistivity tomography in this paper, evaluate and analyze the ability of this technique to finely characterize and quantitatively evaluate the pollution plume through application examples. The study shows that the monitoring technology designed in this paper has good ability to portray the pollution plume formed by small leakage from gas stations, the boundary of the pollution plume formed by secondary repeated leakage, and the diffusion process of the pollution plume caused by the change of the groundwater level; and the inverted three-dimensional spatial resistivity data of the pollution plume and the oil content-resistivity model can be used to estimate the three-dimensional spatial oil content of the plume and the total leakage volume. Based on the time series inversion of the three-dimensional resistivity data, a leakage level criterion is constructed based on the concept of grading. The research paper plays an important role in promoting the three-dimensional fine characterization technology of underground organic matter pollution plumes.
ISSN 1004-2903 (Print)
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