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Karst spring water dynamic characteristics and its response to atmospheric precipitation are of great significance for water resources utilization under the background of climate change. This paper selects Longzici spring area, North China, as the study area. Based on a long series of spring water flow and precipitation data, the dynamic characteristics of spring flow were analyzed and the numerical simulation of the groundwater flow model was established. The results show that the groundwater kept the sustained decline over the past decades which is in a negative equilibrium state, with a storage variable of − 2.26 million m3/year. The sensitivity of spring flow to precipitation under different precipitation scenarios shows that the water level changes in the recharge and drainage areas are similar about (3–5 cm) and slightly larger than that in the runoff area(1.5 cm) when minimum rainfall (287.24 mm) happens. When the precipitation is at its maximum (867.66 mm), the water level change in the runoff area can reach 95 cm which is much larger than those in the recharge and discharge areas. The results indicate that Longzici karst spring has a relatively good regulation water resource capacity and the runoff area is more sensitive which plays an important role in response to climate change. [ABSTRACT FROM AUTHOR]

The seismic sedimentology is an emerging inter-discipline originating from the seismic stratigraphy and sequence stratigraphy. However, implementation of the seismic sedimentological research is found with high difficulties, due to influences imposed by structural and depositional background data (including strong reflections). In this paper, seismic records are regarded as a combination of the reflection from the depositional background and lithological data volumes, and moreover, the seismogram of the depositional background data is characterized by the low frequency and stable phase. Subsequently, the Kernel Hebbian Algorithm (KHA) has been modified to remove the influence of the depositional background data. The seismic trace data are used as the training set, and an innovative attempt has been made to incorporate the Ricker wavelet kernel function. Finally, a depositional background data volume extraction methodology with respect to input of higher-dimension seismic data has been developed, on the basis of the Modified KHA (MKHA), so as to obtain the lithological data volume. Utilizing the unsupervised online learning capabilities of the MKHA, iterative calculation of Kernel PCA can greatly reduce the computational complexity and can be adapted to big data problems. This paper introduces the Ricker wavelet kernel function to transform the original seismic data into the feature space through the inner-product operation, extract the non-linear features, and solve the problem that the seismic data of the original sample space is linearly inseparable. The seismic sedimentological analysis based on the lithological data volume that is able to reflect hidden sand bodies can achieve elaborate carving of the reservoir. The proposed method has been tested in Working Block A of the East-1 district in the Sulige gas field, the Ordos Basin, China. The case study demonstrates that the presented method is capable of efficiently removing the depositional background data, and making great contributions to improving accuracy of the seismic sedimentological analysis of the effective reservoir, with the help of higher-dimension seismic data. [ABSTRACT FROM AUTHOR]

Fracture of high-level extra thick and hard roof (ETHR) above the coal seam is the main reason for the frequent occurrence of mine dynamic disasters such as mine earthquake and rock burst. In order to address this problem, the ground fracturing technology was proposed in this paper to presplit the high-level roof. The FLAC numerical model was established to study the dynamic response of the ETHR before and after fracturing. The simulation results show that: The existence of hydraulic fracture can effectively reduce the first breaking span of ETHR, and slow down the stress and elastic deformation energy concentration of coal and rock mass on both sides of goaf. In order to ensure the economical and effective opening of prefabricated cracks, the comprehensive influence of tensile stress zone and induced stress between cracks should be fully considered in the design of crack spacing. Finally, the field test of hydraulic fracturing was carried out in 63up06 working face in Dongtan coal mine in China. The results of microseismic monitoring showed that there were only 4 strong mine earthquake events of magnitude 2.0 that happened in the first 400 m of excavation, compared with the adjacent working face, the number of large energy mining earthquake events decreased significantly. It showed that the ground fracturing effectively controlled the high and thick strata and verified the feasibility of the ground fracturing technology. The research results can provide some guidance for the treatment of mine earthquake and rock burst in similar working face. [ABSTRACT FROM AUTHOR]

As an important resource for human survival, soil plays an important role in maintaining productivity, environmental quality, animal and plant health, etc. Soil quality evaluation, as a decision-making tool to improve understanding of soil quality, can effectively indicate soil status. Mu Us sandy land of Daji Khan in northern Shaanxi Province is one of the serious desertification areas in China. The phenomenon of soil erosion and ecological deterioration is extremely serious. Therefore, it is urgent to strengthen to pay attention to the research of Mu Us sandy land, to help the restoration of damaged soil, and to build a powerful soil ecosystem. In this paper, the soil quality in the process of development and utilization of the Mu Us sandy land was evaluated based on fuzzy sets for the purpose of sustainable utilization of compound soil. Based on soil structure and soil fertility, 16 evaluation indexes of soil quality in Mu Us sandy land were screened, and then the evaluation index system of soil quality was constructed. The fuzzy multi-objective decision-making model based on fuzzy sets was used to comprehensively evaluate the soil quality from 2013 to 2019. We calculated that the year-on-year growth rates of soil quality from 2013 to 2019 are 13.56, 0.16, 12.81, 33.84, 9.68, and 14.80%, respectively. The results showed that the overall soil quality in the study area showed a trend of increasing year by year, and the year-on-year increase was the largest in 2017. Meanwhile, the reasons for the sudden increase in soil quality in typical years were analyzed. The results showed that the dominant factor of this phenomenon was the comprehensive influence of soil fertility. Furthermore, the relationship between soil fertility and cultivated horizon in typical years was analyzed one by one, and the specific factors affecting soil fertility were discussed. [ABSTRACT FROM AUTHOR]

Yilong Lake is the southernmost plateau freshwater lake in China. The health of its watershed ecosystem is of special strategic significance to maintain the ecological security and ensure the sustainable development of regional economy and society. This paper analyzed the characteristics of landscape type in Yilong Lake Basin of 1990, 1995, 2000, 2005, 2010, 2015 and 2018 and discussed the impact of landscape pattern type changes and its effect on ecosystem services values (ESV). The results showed that: (1) The landscape types of Yilong Lake are mainly forest land and the largest dynamic degree of comprehensive 1andscape type in the six stages is 2010–2015 and the smallest is 2015–2018. (2) Spatially, the most frequent conversion was arbor forest land, which turned to shrub forest land and garden land. The rapid expansion of construction land and transportation land were turned by cultivated land area. (3) Temporally, from 1990 to 2018, the total ESV also increases year by year, and the regional distribution of high ESV is consistent with the distribution of water areas and gardens. The comprehensive analysis shows that the implementation of governance projects such as ecological protection and governance of Yilong Lake surface mountain are conducive to increase the landscape types and the total ESV. [ABSTRACT FROM AUTHOR]

Identification of volcanic lithofacies is critical for reservoir exploration and a major difficulty in China's Liaohe oil field. In this paper, we present a fractal analysis method for identifying volcanic facies by estimating the fractal dimension of logging data. The fractal properties of lithofacies logging curves are explored, as well as the categorization scheme of volcanic lithofacies in the eastern sag of the Liaohe basin. Five logging curves impacted by volcanic lithofacies from four wells in the Liaohe basin's eastern depression were chosen. The Box-counting dimension is used to develop a logging lithofacies identification criterion. Furthermore, we calculated the fractal dimension of logging curves using box-counting dimension methods. [ABSTRACT FROM AUTHOR]

Recently, special attention has been drawn to the high-salt argillaceous dolomite reservoir in Jianghan basin, China due to its abundant oil resources with complex geological conditions. However, the current production methods used to develop this reservoir are not efficient with low throughput. Hence, the purpose of this paper is to explore the main possible reasons affecting the oil well productivity and determine suitable field development method for the target oilfield through experimental and numerical simulation approaches. The mercury injection capillary pressure (MICP) test results indicate that the average pore radius of samples is 0.0144 μm, and pore size distribution (PSD) results from MICP indicate that single peaks appeared in the PSD curves of the pore type samples. Permeability peaks of the samples range from 0.01 to 0.03 μm, and mesopores make most of the permeability contribution of the samples, which also reveals the low-permeability and porosity characteristics of the target oilfield. The results of core stress sensitivity tests show that the largest permeability damage rate is 98.97% with an average permeability damage rate of 98.37% while the maximum porosity damage rate is less than 10% with an average damage rate of 5.57% during the process of depressurization. The results of Non-Darcy percolation experiment indicate that threshold pressure gradient testing by water is about 0.03 MPa/m, which is close to the actual situation of the target oilfield. Numerical simulation method that considers the impact of threshold pressure gradient and stress sensitivity were established to study flooding patterns deployment for the research area. The simulation results show that performing water alternating gas flooding (WAG) by using CO2 is recommended for the development of the high-salt reservoir with inverse five-spot flooding pattern made up of 400 m well spacing in X-direction and 150 m row spacing. [ABSTRACT FROM AUTHOR]

Tight glutenite reservoirs characterization and effective hydrocarbon-bearing formation identification faced great challenge due to ultra-low porosity, ultra-low permeability and complicated pore structure. Fracturing fracture-building technique always needed to obtain deliverability because of poor natural productive capacity. Pore structure characterization and friability prediction were essential in improving such type of reservoir evaluation. In this study, fractured tight glutenite reservoirs in Permian Jiamuhe Formation that located in northwest margin of Junggar Basin, northwest China, were chosen as an example, and 25 typical core samples were drilled and simultaneously applied for mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR) and whole-rock mineral X-ray diffraction experiments. A novel method of synthetizing pseudo-pore-throat radius (Rc) distribution from porosity frequency spectra was established to characterize fractured formation pore structure. Quartz and calcite were considered as the fragile mineral, and rock mineral component ratio method was used to predict brittleness index. Meanwhile, the statistical model raised by Jin et al. (SPE J 20:518–526, 2015) was used to predict two types of fracture toughness. And then, brittleness index and fracture toughness were combined to characterize tight glutenite reservoirs friability. Combining with maximal pore-throat radius (Rmax, reflected rock pore structure) and friability, our target formations were classified into four clusters. In addition, relationships among pore structure, friability and daily hydrocarbon production per meter (DI) were analyzed, and a model to predict DI from well-logging data was established. Comparison of predicted DI with the extracted results from drill stem test (DST) data illustrated the reliability of our raised models. This would be valuable in determining optimal hydrocarbon production intervals and formulating reasonable developed plans. [ABSTRACT FROM AUTHOR]

The South Jingyang tableland, located in Shaanxi Province, China, is composed of loess deposits. Agricultural irrigation in this area has caused the continuous rise of the groundwater table, which triggered a series of loess landslides. Although extensive research has been conducted on the effect of rising groundwater tables on induced loess landslides, less is known about the groundwater table distribution. This study jointly investigated the distribution of the groundwater table in the South Jingyang tableland using boreholes, electrical resistivity tomography (ERT), and laboratory tests. A qualitative analysis between the apparent resistivity and the water content was estimated at different depths, using the borehole data and ERT inversion data. A quantitative relationship between the resistivity and the water content was established in the laboratory tests. A combination of the qualitative analysis of the inversion results and the quantitative relationship was used to determine the distribution of the groundwater table. The groundwater table is present at the depth where the water content of the loess is 30% (liquid limit of loess) and the resistivity is 28.35 Ω m. The groundwater table elevation in the southern study area is higher than that of the northern study area and decreases in a stepwise gradient from south to north. This study not only identified the distribution of the groundwater table in the South Jingyang tableland, but also makes up for the limitation and inaccuracy in determining groundwater tables by relying solely on the borehole information or inversion results of ERT. The ascertained distribution characteristics of the groundwater table provides a basis for the analysis of the formation mechanism of landslides. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) plays a key role in water cycle and energy balance, and the construction of large areas of vegetation in the Yellow River Basin (YRB) will cause an increase in regional ET and changes in water use in the basin. Based on GLEAM evapotranspiration products, meteorological stations and land use data, this study used slope trend analysis, Mann-Kendall (M-K) test and partial correlation analysis to analyse changes in evapotranspiration and water use in the YRB before and after reforestation from 1980 to 2019. The results showed that the annual average ET of the YRB from 1980 to 2019 ranged from 363 to 447 mm with an average change rate of 10.2 mm/10a. The actual evapotranspiration/potential evapotranspiration (ET/PET) growth rate of the YRB decreased after the Grain for Green Project (GGP), and the actual evapotranspiration/precipitation (ET/P) decreased extremely significantly. Water use efficiency in the YRB was significantly reduced, and grassland was subjected to greater water stress. This study provides scientific support for future water balance, landscape restoration, ecological protection and quality development of the YRB. [ABSTRACT FROM AUTHOR]

The velocity is not uniformly distributed in ST area of Dongying Depression in China, which varies both horizontally and vertically. In order to obtain accurate time-depth results, it is necessary to find an appropriate velocity model for time-depth conversion according to the actual situation of the study area. First, the characteristics and main affecting factors of velocity variation in the study area were analyzed. Analysis results showed that the velocity is obviously multi-segment in the vertical direction and zoned on the plane, with a larger velocity in the northern part of Shengbei fault and a smaller velocity in the southern part. The main factors affecting the velocity distribution are the burial depth or compaction, sedimentary facies distribution and lithological composition. Then, the velocity model was established by using checkshot data of 30 wells after making synthetic records. We proposed an integrated velocity modeling method that considers the velocity distribution characteristics and matches the geological characteristics well. Above the target layer, the polynomial fitting method was used to calculate the depth of the bottom of Es3. Then, segmental V = v0/k functions were fit to calculate the thickness of each layer. Subsequently, the stripping method was used to calculate the bottom depth layer by layer. Using this method in the study area effectively reduced uncertainty, improved accuracy of time-depth conversion and accurately understood the lateral structure and stratigraphic pattern of the basin, which could facilitate a rapid search for structural traps. [ABSTRACT FROM AUTHOR]

The coalbed methane content (CMC) is an important parameter to evaluate the degree of coalbed methane enrichment, and also an important reservoir parameter to calculate coalbed methane resources, productivity prediction and reservoir simulation. Accurately identifying the distribution of CMC is crucial to the exploration of CBM. In this study, we developed a prediction method for the CMC distribution via seismic techniques identification of key geological parameters such as structure, coal thickness and sedimentation. Firstly, the geological factors that control the generation and preservation of CBM in the study area are quantitatively characterized by using five parameters: surface ( X 1 ), residual ( X 2 ), dip ( X 3 ), coal thickness ( X 4 ) and the ratio of sand to mud ( X 5 ). Secondly, the geological parameters are extracted by seismic structure interpretation and inversion prediction technology. Thirdly, the key geological parameters of CMC are screened out by grey correlation analysis. Finally, the functional relationship of CMC and the key geological parameters is established to predict the CMC distribution. The method is applied to the CMC distribution prediction of two coal seams of a study area in the southern Qinshui Basin, China. Results show that different coal seams differ in key geological parameters of CMC, resulting in various CMC distribution laws. The CMC prediction method based on the key geological factors can effectively delineate the CBM enrichment area in the study area, providing important reference for the CBM exploration and development. [ABSTRACT FROM AUTHOR]

A quaternary unconsolidated confined aquifer is one of the main sources of water inrush in Huaibei coalfield. Water abundance evaluation of the aquifer is the key to guiding water prevention in coal mining. Aiming at the issue of water abundance in the unconsolidated confined aquifer, a novel evaluation model was established based on three evaluation indexes: the depth of water level, the depth of roof and the sedimentary characteristics. Among them, the sedimentary characteristics were quantified in comprehensive consideration of three aspects: the aquifer lithology, sedimentary thickness of rock stratum and sedimentary sequence. Then, the evaluation model was validated with an accuracy of 90.57% and was applied to the Zhuxianzhuang coal mine in the Su-Lin mining areas, so the zoning prediction map of water abundance of the unconsolidated confined aquifer was obtained. The results show that medium water abundance areas are scattered in the middle part of the mine and other areas are of weak or extremely weak water abundance. The distribution characteristics of water abundance obtained from the actual detection results are consistent with that predicted by the model, which further proves the reliability of the model. The findings of this research provide a new method for the water abundance evaluation, which is of great importance to ensure safety production of coal mine under unconsolidated confined aquifer in the Su-Lin mining areas, as well as other similar mining areas. [ABSTRACT FROM AUTHOR]

With the development of economy, the urbanization process is accelerated and the infrastructure construction is increased, which leads to the widespread occurrence of landslides in mountain areas all over the world. However, due to the complex geological environment or some other reasons, the lack of landslide-related data in some mountainous areas makes it more difficult to predict landslides. At the same time, the existing models have different prediction effects in different regions, and it is difficult for a single model to objectively and accurately evaluate landslide hazard. The purpose of this research is to complete the landslide hazard assessment (LHA) in data-deficient areas by proposed a combination model with help of remote sensing (RS) and geographic information system (GIS) technology. Firstly, 146 landslides and 10 LHA conditioning factors in Tumen City were obtained by using RS, GIS and field investigation. To increase the amount of model training data, 386 landslides (including 146 landslides in Tumen City) in some areas of Yanbian Korean Autonomous Prefecture with similar landslide conditions to Tumen City were obtained. Secondly, three combination models for LHA are proposed, which make full use of the effective information provided by logistic regression (LR), artificial neural network (ANN) and support vector machine (SVM), and the evaluation effect and applicability of the three combination models are discussed. Finally, the three combination models and three single models of logistic regression (LR), artificial neural network (ANN), support vector machine (SVM) are analyzed and compared through the overall accuracy (OA), confusion matrix and landslide density. The results show that it can effectively complete the landslide hazard assessment in data-deficient areas with help of RS and GIS, and the three combination models proposed in this research are superior to the other three single models, and the evaluation effect of the LA-SVM combination model is the best. [ABSTRACT FROM AUTHOR]

After waterflooding, the distribution of the remaining oil in low-permeability porous reservoirs is quite complicated. Strong heterogeneity of formations makes the waterflooding performance more complex. Therefore, accurate prediction and evaluation of the spatial distribution of the remaining oil and the waterflooding performance of low-permeability reservoirs are essential for understanding the waterflooding process and improving oil recovery. In the study, an empirical method is proposed to predict waterflooding performance combined with static and dynamic data for porous reservoirs. Static data, including logging curves, core porosity and permeability data, are adopted to classify the formation into three hydraulic flow units (HFUs). The proportions of the thicknesses of different HFUs (HFUp) are proposed to characterize the remaining oil distribution. In addition, a waterflooding performance prediction method based on the Koval method was built using dynamic production data. The results show that the HFUp plays the key role in predicting the distribution of the remaining oil in the research well group. The K-factor-based waterflooding prediction method is highly correlated with the history matching in low-permeability waterflooded layers. The study also found Type 3 HFUp shows a great effect in predicting the duration of the low water-cut oil production. Therefore, the empirical method can provide a quick and intuitive evaluation of waterflooding performance in space and time of low-permeability waterflooded reservoirs with the local average K-factor and the HFUp results. The empirical method is of great significance to evaluate the remaining oil, infilling of well pattern, and improving oil recovery. [ABSTRACT FROM AUTHOR]

Unsaturated soil properties such as soil–water characteristic curve (SWCC) and shear strength are required for seepage and stability flow analyses in various geo-engineering infrastructures. Microbial-induced calcite precipitation (MICP) has been recently adopted for enhancing strength of soils however, with rare focus on improvement in unsaturated soil properties of granitic residual soil. It is known that granite residual soil exhibits unique disintegration properties upon interaction with water. The objective of this study is to investigate the unsaturated properties under different vertical stresses (0, 100, 200 and 300 kPa) for MICP treated granitic residual soils. Further, microstructural characterization of MICP treated soil was conducted to analyse its water retention and shear strength, so as to provide theoretical basis for engineering application of MICP in strengthening granite residual soil. Pressure plate apparatus and FDJ-20 quadruple shear strength apparatus were utilized to obtain SWCCs and shear strength, respectively. Based on the result, it can be concluded that the treatment by MICP is found to enhance the air entry value of granitic residual soil. In addition, MICP treated soils possess higher water content than untreated soil at near-saturated condition. This is due to calcite precipitation on surface of grains and carbonate formation at contact points, which in turn reduces void ratio. However, the difference in water retention reduces with an increase in suction and also confining stress. It is possibly due to breakage of carbonate bonds at contact points at higher stresses. After five times grouting, the effective cohesion, internal friction angle and matric suction angle is found to increase very significantly. [ABSTRACT FROM AUTHOR]

Experimental study of logging petrophysical parameters is very important for the establishment of logging evaluation model of coalbed methane reservoir. The acoustic and resistivity measurements of coal rock samples taken from the southern Qinshui Basin in China were measured under dry and saturated conditions of different salinity solutions. The variation laws of acoustic velocity and waveform with saturated salinity were analyzed. The changes of resistivity with temperature and pressure conditions were also analyzed. With the increase in salinity, acoustic velocity showed parabolic attenuation characteristics. The fluid content of coal samples can be judged by the acoustic wave. The waveform of dry coal sample presented multiple excitation state, and the waveform had larger fluctuation and smaller amplitude. The waveform of saturated salinity coal sample presented stable and smooth fluctuation characteristics. The resistivity of coal rock decreased exponentially with the increase in pressure. The property of fluid in pores can be judged by the sensitivity of resistivity of coal rock to temperature. [ABSTRACT FROM AUTHOR]

The existing researches for leaf area index (LAI)-based Penman–Monteith evapotranspiration (ET) model (PML) are mostly carried out at yearly scale and the analysis of effects of seasonal change and different underlying surface conditions on model parameters is scarce. This study emphasizes on the influences of seasonal change and diverse land surface conditions on ET by optimizing the sensitive parameters, namely soil evaporation coefficient f and maximum stomatal conductance gsx, with particle swarm algorithm. This analysis is based on the observations of eight flux stations in China. The model performance is reasonable with a best Pearson r of 0.87. The seasonal calibration results indicate parameters change evidently in different seasons and have obvious spatial heterogeneity. The seasonal calibration method has an obvious effect on improving the ET accuracy in spring, which is mostly influenced by regional temperature and relative humidity. This study further demonstrates the need to dynamically adjust model parameters over time with PML model for evapotranspiration simulations, rather than simply setting these parameters to constants depended on subsurface conditions such as land use type. [ABSTRACT FROM AUTHOR]

The soil layer is the most important structure for green roof runoff reduction and vegetation growth. The mechanisms of runoff reduction and water content of green roofs with varying soil depth and saturated water content (θs) under dry–wet cycles are not well understood. Field and numerical methodologies were adopted for investigation in this study. The green roof drainage and water content were observed for a given period (i.e., August 2020 to July 2021). A numerical model was calibrated and validated for the analysis of annual runoff reduction and water stress with different θs and soil depths. Based on climate in southern China, the green roof's annual runoff reduction rate (ARR) (100 mm soil) was 33%, and the annual water stress was 168 days. With an increase in θs by 0.1 mm3/mm3, the ARR of green roofs increased by an average of 5% while the water stress was reduced by an average of 32 days. With an increase in soil depth by 100 mm, the average ARR increased by 4%, whereas the average water stress was reduced by 6 days. It was shown that the runoff reduction is enhanced with an increasing θs and soil depth during a longer antecedent dry weather period, but it had no significant effect on runoff reduction during back-to-back rainfall events. Increasing soil depth had no significant improvement in runoff reduction and water stress beyond a certain point. Consequently, the optimal structural configuration of green roofs was considered as a soil depth of 200 mm (θs of 0.5 mm3/mm3). [ABSTRACT FROM AUTHOR]

China geological survey has conducted two hydrate expeditions for two gas chimney structures (GC1, GC2) in the Qiongdongnan Basin, South China Sea, where the fluid migrations vary significantly. Although massive hydrates were recovered both in the seepage pathways above GC1 and GC2, the free gas distributions in seeping seafloor hydrate stability zone (HSZ) remain controversial. Previous studies confirm that structure I (sI) and structure II (sII) hydrates occur through the whole seepage pathways, and free gas accumulates below the base of methane hydrate stability zone (BHSZ). In fact, free gas and gas hydrates coexist in the whole seepage-gas chimney system. The quantitative estimation of the fluid distribution is significant for studying the heterogeneous fluid migration in the seepages. In this study, Archie formula and three-phase Biot-type equation are modified to invert fluid concentrations for the whole well sections, in which brine, free gas, gas hydrate and matrix are considered as separate phases. The results indicate that the bottom simulating reflector is the boundary of an increasing gas concentration and a decrease hydrate concentration, instead of the interfaces of the hydrate and free gas in most areas. And hydrate occurrence is closely related to the micro-fault in the gas chimney. By comparing the fluid distribution between GC1 and GC2, more free gas associated with gas hydrates is accumulated in the seepage pathways in HSZ in GC1 where less free gas occurred below the BHSZ. Gas-bearing fluids in GC1 are considered to be very active in historic time, but they nearly stop flowing now, and the remaining gas cannot form hydrates in the hydrate-saturated pores, while the fluids in GC2 tend to convert to hydrates till now, and it is an active or younger fluid system. Free gas is the important intermediate medium for revealing this phase transition and exerts a significant control on the timescales associated with phase equilibrium variation processes. It is the first study revealing the relationship between the fluid distribution and the mobility of the seepage-gas chimney system in the study area, which also provide a new insight for estimating hydrate resource. [ABSTRACT FROM AUTHOR]

The identification of gas content is very important for exploration and development of coalbed methane (CBM) reservoirs. As a kind of gas-bearing reservoirs in coal seam, CBM reservoirs usually show strong heterogeneity, which makes the gas content varies greatly in the strata. What's more, the thin interlayer that is common in coal-bearing formation makes it difficult to predict the favorable gas-bearing distribution based on conventional methods. In this study, a seismic waveform indication inversion method was applied to reveal the gas content of No. 8 coal seam reservoirs in the Upper Carboniferous Benxi Formation of the DJ area in the eastern of the Ordos Basin, China. The first step of this method is to calculate the p-wave impedance inversion volume of No. 8 coal seam. The second step is to build the correlation between elastic parameters and gas content in No. 8 coal seam. Through the statistical analysis based on velocity, density, p-wave impedance and measured gas content data of 16 wells, the fitting formula between p-wave impedance and gas content is obtained, with a highest correlation coefficient up to 96%. The third step is to calculate the gas content data volume from the p-wave impedance inversion volume by the above fitting formula, and then the quantitative plane distribution of gas content in No. 8 coal seam can be predicted. The prediction results indicate that the gas content of No. 8 coal seam can be divided into two Classes. To verify the reliability of the inversion results, the production data of well X11 was applied to verify the gas content which located in the Class I area. The application of seismic waveform indication inversion has provided a precise prediction for the spatial distribution of gas content in CBM reservoirs, serving as a basis for locating and designing wells for CBM development. [ABSTRACT FROM AUTHOR]

Over the past 50 years, China has implemented a series of ecological construction projects in the Loess Plateau that have significantly decreased the runoff and sediment from the Yellow River, and it plays an important role in check dams and terraced fields. In this study, the hydrological characteristics of check dams and terraces are used to distinguish their runoff generation pattern. Combined with different runoff generation patterns, runoff generation models were built, and quantitative analysis was conducted on the runoff reduction situation of check dams and terraced fields. Chenggou River Basin, in the Loess Plateau Zhuli River System's second tributary, was selected as an example for analyzing quantitatively the influence of check dam and terraced fields on the runoff production process. Twenty-nine rainfall-flood events from 2013 to 2017 were used to evaluate the effect of the runoff generation model, and the results showed that the built model could well simulate the runoff generation in the basin with many check dams and terraces in which runoff relative error of the model was less than 10%. The effect of check dams and terraces on runoff was studied by setting different scenarios. The results show that the dam system can intercept over 50% of the runoff yield of the basin. Terraced fields can enhance the water storage capacity of the basin and reduce the runoff of the basin, and intercept over 10% of the runoff yield of the basin. [ABSTRACT FROM AUTHOR]

The low-frequency component of seismic data is an inevitable part to obtain absolute P-impedance ( I p ) and V p / V s ratio of the subsurface, especially for the reservoir sweet spot. In this work, we train the deep feedforward neural network (DFNN) with band-pass seismic data and well log data to obtain favorable low-frequency components. Specifically, the Bayesian inference strategy is first applied to the pre-stack constrained sparse spike inversion process, obtaining an "initial" inverted band-pass parameters, which are subsequently used as input when applying the DFNN algorithm to predict low- and band-pass parameters. Moreover, the high linear correlation coefficient between the DFNN-based inversion results and the realistic well logging curves of the blind wells demonstrates that the DFNN-based inversion scheme exhibits strong robustness and good generalization ability. Ultimately, we apply the proposed DFNN-based inversion strategy to a tight sandstone reservoir located at the Sichuan basin field from onshore China. Both low- and band-pass I p and V p / V s inverted for the clastic formation of the Sichuan basin show a strong correlation with the corresponding I p and V p / V s logs. [ABSTRACT FROM AUTHOR]

The tilt angle (i.e., TDR) provides an efficient way to recognize the horizontal locations of multi-source geological bodies at different depths and inclination angles. The tilt-depth method was initially derived by applying magnetic formulas and used to calculate the depth of magnetic sources. Recently researchers have attempted to extend this method to interpret depths in gravity field data. The tilt-depth method of gravity anomalies (i.e., GTilt-depth) could capture the depth of a buried source effectively, which makes it superior at deciphering the basement relief. Meanwhile, Tilt-Euler deconvolution (i.e., Euler deconvolution of TDR) has been utilized for estimating a source's position from gridded data automatically, which requires no structural index. However, analytical singularities can be produced when performing inversion with the Tilt-Euler deconvolution owning to the derivatives of TDR being incalculable when the horizontal derivative is zero. The improved Tilt-Euler deconvolution provided an efficient way to eliminate analytical singularities and obtain more stable solutions. The results from the theoretical model show that the GTilt-depth method and improved Tilt-Euler deconvolution could be applied to calculate the buried depths more accurately and effectively. Application of these methods shows that they are able to capture more detailed features, and provide more straightforward and accurate results of depth, than traditional methods. Furthermore, the results obtained from the gravity data in Sichuan Basin show that the basement depth ranges from 3 to 11 km, and 3 to 7 km in the central uplift, which contains a local depression with a depth of 8 km. The basement exhibits a general pattern of "shallow in middle and deep in east and west", which is consistent with the results revealed by gravity-seismic jointly interpreted profile. This research provides a better indication of the basement structure when interpreting the regional geology in Sichuan Basin. [ABSTRACT FROM AUTHOR]

The element content obtained by X-ray fluorescence (XRF) mud-logging is mainly used to determine mineral content and identify lithology. This work has been developed to identify dolomite, granitic gneiss, granite, limestone, trachyte, and rhyolite from two wells in Nei Mongol of China using back propagation neural network (BPNN) model based on the element content of drill cuttings by XRF analysis. Neural network evaluation system was constructed for objective performance judgment based on Accuracy, Kappa, Recall and training speed, and BPNN for lithology identification was established and optimized by limiting the number of nodes in the hidden layer to a small range. Meanwhile, six basic elements that can be used for fuzzy identification were determined by cross plot and four sensitive elements were proposed based on the existing research, both of which were combined to establish sixteen test schemes. A large number of tests are performed to explore the best element combination, and the result of experiments indicate that the improved combination has obvious advantages in identification performance and training speed. The author's pioneer work has contributed to the neural network evaluation system for lithology identification and the optimization of input elements based on BPNN. [ABSTRACT FROM AUTHOR]

The quantitative analyses of karst spring discharge typically rely on physical-based models, which are inherently uncertain. To improve the understanding of the mechanism of spring discharge fluctuation and the relationship between precipitation and spring discharge, three machine learning methods were developed to reduce the predictive errors of physical-based groundwater models, simulate the discharge of Longzici spring's karst area, and predict changes in the spring on the basis of long time series precipitation monitoring and spring water flow data from 1987 to 2018. The three machine learning methods included two artificial neural networks (ANNs), namely multilayer perceptron (MLP) and long short-term memory–recurrent neural network (LSTM–RNN), and support vector regression (SVR). A normalization method was introduced for data preprocessing to make the three methods robust and computationally efficient. To compare and evaluate the capability of the three machine learning methods, the mean squared error (MSE), mean absolute error (MAE), and root-mean-square error (RMSE) were selected as the performance metrics for these methods. Simulations showed that MLP reduced MSE, MAE, and RMSE to 0.0010, 0.0254, and 0.0318, respectively. Meanwhile, LSTM–RNN reduced MSE to 0.0010, MAE to 0.0272, and RMSE to 0.0329. Moreover, the decrease in MSE, MAE, and RMSE was 0.0397, 0.1694, and 0.1991, respectively, for SVR. Results indicated that MLP performed slightly better than LSTM–RNN, and MLP and LSTM–RNN performed considerably better than SVR. Furthermore, ANNs were demonstrated to be prior machine learning methods for simulating and predicting karst spring discharge. [ABSTRACT FROM AUTHOR]

The Southwestern area of Fujian Province in China contains a major metallogenic belt. There have been three major tectonic movements since the Late Paleozoic, and the thrusts here are the main mineral deposits. These occurred between the Early Carboniferous and Late Permian eras. Due to dramatic undulations in the surface and associated complex underground structures, a single geophysical method cannot provide reliable imaging results. This is largely due to difficulties in data acquisition and processing. Seismic exploration provides one example. Using this method, raw shot gathers have a low signal-to-noise ratio because of the undulations in the topography. Furthermore, strong lateral velocity variation makes the migration process exceedingly difficult. This means that interpretations of the resulting reflection seismic profile give rise to uncertainty. For this reason, two-dimensional reflection seismology and controlled source audio-frequency magnetotellurics (CSAMT) electromagnetic sounding techniques were performed. After initially completing conventional processing on the seismic reflection data, subsequent pre-stack depth migration (PSDM) over the rugged topography yielded a much better image. It was able to identify thrust faults and magma intrusions. Then, using CSAMT, inversion was conducted with the same topography as the seismic reflection. By combining the migrated seismic profile, inverted resistivity profile, and borehole data, a vertical geological model was constructed. This proved the existence of an overlapped thrust, and it also indicated the possible presence of deeper mineralization. [ABSTRACT FROM AUTHOR]

With the development of oil and gas exploration, the conventional seismic migration imaging technology based on the isotropic assumption no longer meets our current requirements for high-resolution images. Migration in anisotropic media has become an essential requirement for oil and gas exploration. Marine seismic exploration has gradually entered the wide-azimuth and high-density seismic data acquisition stage. However, even for current large high-performance computer clusters, it is still very difficult to implement pre-stack depth migration based on shot gathers. Thus, we present a double-square-root (DSR) equation based on three-dimensional (3D) pre-stack depth migration in midpoint-offset domain for a wide-azimuth dataset in transversely isotropic media with a vertical symmetry axis (VTI media). Considering VTI media, the DSR migration requires extensive memory and computation; we adopted the phase-shift plus interpolation approach to improve the computational efficiency. Then, we extract the angle-domain common-image gathers (ADCIGs) during DSR migration. For real large-scale seismic data, we designed an effective parallel implementation of 3D DSR migration with ADCIGs outputs. Finally, we applied the proposed angle-domain VTI DSR migration on wide-azimuth SEG/EAGE salt dome-based data and real data from the China South Sea. Numerical and practical data illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Thin interbeds are typical reservoirs in eastern China. Thin layers and fractures bring huge challenge to fluid identification in anisotropic reservoir. This study focuses on thin-fractured reservoirs and amplitude attributes of shear-wave splitting, and consequently predicted fluid type in fractured reservoir based on the response of fast and slow S-waves to fluids. 3D HTI viscoelastic equation was employed to analyze amplitudes of split S-waves through fluid-filled and fractured media, including oil- and water-saturated synthetic models. Similar to velocity anisotropy, amplitude anisotropy was proposed to avoid the calculation of S-wave quality factor. Amplitude ratio and substation derived from amplitude anisotropy were used to identify fluid type. Example from the Luojia area of Shengli oilfield was used to demonstrate the effectiveness of the inversion method. Results show that amplitude ratio and amplitude subtraction are useful to distinguish fluids, while the former works better than the latter. [ABSTRACT FROM AUTHOR]

Structural and stratigraphic discontinuities, such as faults and channels, generally contribute to the construction of traps and reservoirs. Spectral decomposition can utilize the sensitivities of different frequency components to different geological conditions to identify these geological anomalies. The sparse inverse spectral decomposition (SISD) involves a sparse constraint of time–frequency spectra, and one critical parameter is the sparsity which determines the time–frequency resolution. A small sparsity gives a low temporal resolution result that cannot be used for thin-bed detection. Conversely, a large sparsity provides a high-resolution result, but it may lose weak reflection signals. The complex geological conditions in the subsurface will lead to some difficulties in detecting the discontinuities by using the SISD method with a fixed sparsity. To address this issue, we propose multi-sparsity-based spectral attributes by fusing the amplitude spectra results of three different sparsities to detect subsurface discontinuities. Compared with the fixed sparsity, the multi-sparsity-based spectral attributes can detect more geological details and highlight geological edges more clearly. The application on a 3D real data with an area of 230 km2 from deep formation in Northwest China exhibits its effectiveness in discontinuity detection. The proposed method can detect the weak or small hidden geological details more and better than the fixed sparsity method, suggesting that it may serve as a future tool for detecting the distribution of geological abnormalities in subsurface. [ABSTRACT FROM AUTHOR]

In the areas where carbonate rocks expose to the near surface, there are several intractable issues in conventional surface seismic, including (1) weak reflection energy, (2) complex wave field and (3) serious static correction. Therefore, the seismic imaging result suffers significantly. However, RVSP is able to achieve reflected data with high quality since it generates seismic waves in borehole and receives seismic waves at the surface. In order to verify the applicability of RVSP technique in complex areas, this study carried out a 3D-RVSP seismic experiment in Wulunshan coal field, southwest China. Compared with the surface seismic data, RVSP data show higher signal-to-noise ratio, wider frequency band and weaker surface wave interference. In addition, two imaging methods (conventional CDP transform stack and novel equivalent-surface conversion) were implemented for RVSP data imaging. The imaging results show that the smaller and deeper structures can be revealed better by equivalent-surface conversion method than by CDP transform stack method. Hence, this study demonstrates that RVSP is an efficient method applied in the area with complex surface condition. [ABSTRACT FROM AUTHOR]

We studied variation characteristics of ionospheric total electron contents (TEC) and performance of the International Reference Ionosphere (IRI)-2012 model in predicting TEC at the BJFS (Beijing Fangshan station), China. Diurnal and seasonal variations were analyzed with TEC data derived from dual-frequency global positioning system (GPS) observations along with the solar activity dependence of TEC at the BJFS station. Data interpolated with information from IGS Global Ionosphere Maps (GIMs) were also used in the analysis. Results showed that the IRI-2012 model can reflect the climatic characteristics and solar activity dependence of ionospheric TEC. By using time series decomposition method, ionospheric daily averaged TEC values were divided into the periodic components, geomagnetic activity component, solar activity component and secular trend. Solar activity component and periodic components are supposed to be the main reasons which account for the difference between the GIMs TEC and the TEC from the IRI-2012 model. [ABSTRACT FROM AUTHOR]

The organic reef is a special type of carbonate reservoir which always dominates the spatial distribution, reserves and accumulations of natural gas. However, it is difficult to determine the organic reef's internal structure and gas reservoirs due to numerous adverse factors such as the low resolution of seismic data, depth of burial, strong anisotropy, irregular spatial distribution and complex internal structure. A case study of wavelet decomposition and reconstruction technology applied to elucidate the features of organic reef reservoirs in the Changxing formation from Yuanba gas field shows that the seismic record reconstructed by high frequency signal can adequately describe the internal properties of organic reef reservoirs. Furthermore, the root mean square amplitude ratio of both low and high frequency data obtained from the reconstructed seismic data clearly show spatial distribution of gas and water in reef reservoirs. [ABSTRACT FROM AUTHOR]