Regression analysis and its application to oil and gas exploration:A case study of hydrocarbon loss recovery and porosity prediction,China

In oil and gas exploration,elucidating the complex interdependencies among geological variables is paramount.Our study introduces the application of sophisticated regression analysis method at the forefront,aiming not just at predicting geophysical logging curve values but also innovatively mitigate hydrocarbon depletion observed in geochemical logging.Through a rigorous assessment,we explore the efficacy of eight regression models,bifurcated into linear and nonlinear groups,to accommodate the multifaceted nature of geological datasets.Our linear model suite encompasses the Standard Equation,Ridge Regression,Least Absolute Shrinkage and Selection Operator,and Elastic Net,each presenting distinct advantages.The Standard Equation serves as a foundational benchmark,whereas Ridge Regression implements penalty terms to counteract overfitting,thus bolstering model robustness in the presence of multicollinearity.The Least Absolute Shrinkage and Selection Operator for variable selection functions to streamline models,enhancing their interpretability,while Elastic Net amalgamates the merits of Ridge Regression and Least Absolute Shrinkage and Selection Operator,offering a harmonized solution to model complexity and comprehensibility.On the nonlinear front,Gradient Descent,Kernel Ridge Regression,Support Vector Regression,and Piecewise Function-Fitting methods introduce innovative approaches.Gradient Descent assures computational efficiency in optimizing solutions,Kernel Ridge Regression leverages the kernel trick to navigate nonlinear patterns,and Support Vector Regression is proficient in forecasting extremities,pivotal for exploration risk assessment.The Piecewise Function-Fitting approach,tailored for geological data,facilitates adaptable modeling of variable interrelations,accommodating abrupt data trend shifts.Our analysis identifies Ridge Regression,particularly when augmented by Piecewise Function-Fitting,as superior in recouping hydrocarbon losses,and underscoring its utility in resource quantification refinement.Meanwhile,Kernel Ridge Regression emerges as a noteworthy strategy in ameliorating porosity-logging curve prediction for well A,evidencing its aptness for intricate geological structures.This research attests to the scientific ascendancy and broad-spectrum relevance of these regression techniques over conventional methods while heralding new horizons for their deployment in the oil and gas sector.The insights garnered from these advanced modeling strategies are set to transform geological and engineering practices in hydrocarbon prediction,evaluation,and recovery.

A hydrocarbon enrichment model and prediction of favorable accumulation areas in complicated superimposed basins in China

The geologic conditions of superimposed basins in China are very complicated. This is mainly shown by multi-phase structural evolution, multiple sets of source-reservoir-cap rock combinations, multiple stages of hydrocarbon generation and expulsion from source rocks, multi-cycle hydrocarbon enrichment and accumulation, and multi-phase reservoir adjustment and reconstruction. The enrichment, accumulation and distribution of hydrocarbon is mainly controlled by the source rock kitchen, paleo- anticline, regional cap rock and intensity of tectonic movement. In this paper, the T-BCMS model has been developed to predict favorable areas of hydrocarbon accumulation in complicated superimposed basins according to time and spatial relationships among five key factors. The five factors include unconformity surface representing tectonic balancing （B）, regional cap rock representing hydrocarbon protection （C）, paleo-anticline representing hydrocarbon migration and accumulation （M）, source rock kitchen representing hydrocarbon generation and expulsion （S） and geological time （T）. There are three necessary conditions to form favorable areas of hydrocarbon accumulation. First, four key factors BCMS should be strictly in the order of BCMS from top to bottom. Second, superimposition of four key factors BCMS in the same area is the most favorable for hydrocarbon accumulation. Third, vertically ordered combination and superimposition in the same area of BCMS should occur at the same geological time. The model has been used to predict the most favorable exploration areas in Ordovician in the Tarim Basin in the main hydrocarbon accumulation periods. The result shows that 95% of the discovered Ordovician hydrocarbon reservoirs are located in the predicted areas, which indicates the feasibility and reliability of the key factor matching T-BCMS model for hydrocarbon accumulation and enrichment.

Formation Dynamics and Quantitative Prediction of Hydrocarbons of the Superpressure System in the Dongying Sag

Based on the theory of formation dynamics of oil/gas pools, the Dongying sag can be divided into three dynamic systems regarding the accumulation of oil and gas： the superpressure closed system, the semi-closed system and the normal pressure open system. Based on the analysis of genesis of superpressure in the superpressure closed system and the rule of hydrocarbon expulsion, it is found that hydrocarbon generation is related to superpressure, which is the main driving factor of hydrocarbon migration. Micro fractures formed by superpressure are the main channels for hydrocarbon migration. There are three dynamic patterns for hydrocarbon expulsion： free water drainage, hydrocarbon accumulation and drainage through micro fissures. In the superpressure closed system, the oil-driving-water process and oil/gas accumulation were completed in lithologic traps by way of such two dynamic patterns as episodic evolution of superpressure systems and episodic pressure release of faults. The oil-bearing capacity of lithologic traps is intimately related to reservoir-forming dynamic force. Quantitative evaluation of dynamic conditions for pool formation can effectively predict the oil-bearing capability of traps.

Buoyance-driven hydrocarbon accumulation depth and its implication for unconventional resource prediction

The discovery of unconventional hydrocarbon resources since the late 20th century changed geologists’understanding of hydrocarbon migration and accumulations and provides a solution to energy shortage.In 2016,unconventional oil production in the USA accounted for 41%of the total oil production;and unconventional natural gas production in China accounted for 35%of total gas production,showing strong growth momentum of unconventional hydrocarbons explorations.Unconventional hydrocarbons generally coexist with conventional petroleum resources;they sometimes distribute in a separate system,not coexisting with a conventional system.Identification and prediction of unconventional resources and their potentials are prominent challenges for geologists.This study analyzed the results of 12,237 drilling wells in six representative petroliferous basins in China and studied the correlations and differences between conventional and unconventional hydrocarbons by comparing their geological features.Migration and accumulation of conventional hydrocarbon are caused dominantly by buoyance.Wepropose a concept of buoyance-driven hydrocarbon accumulation depth to describe the deepest hydrocarbon accumulation depth driven dominantly by buoyance;beyond this depth the buoyance becomes unimportant for hydrocarbon accumulation.We found that the buoyance-driven hydrocarbon accumulation depth in petroliferous basins controls the different oil/gas reservoirs distribution and resource potentials.Hydrocarbon migration and accumulations above this depth is dominated by buoyancy,forming conventional reservoirs in traps with high porosity and permeability,while hydrocarbon migration and accumulation below this depth is dominated by non-buoyancy forces(mainly refers to capillary force,hydrocarbon volumeexpansion force,etc.),forming unconventional reservoirs in tight layers.The buoyance-driven hydrocarbon accumulation depths in six basins in China range from 1200mto 4200 m,which become shallowerwith increasing geothermal gradient,decreasing particle size of sandstone reservoir layers,or an uplift in the whole petroliferous basin.The predicted unconventional resource potential belowthe buoyance-driven hydrocarbon accumulation depth in six basins in China is more than 15.71×10^(9) t oil equivalent,among them 4.71×10^(9) t reserves have been proved.Worldwide,94%of 52,926 oil and gas reservoirs in 1186 basins are conventional reservoirs and only 6%of them are unconventional reservoirs.These 94%conventional reservoirs show promising exploration prospects in the deep area below buoyance-driven hydrocarbon accumulation depth.

Pre-Drilling Prediction Techniques on the High-Temperature High-Pressure Hydrocarbon Reservoirs Offshore Hainan Island,China

Decreasing the risks and geohazards associated with drilling engineering in high-temperature high-pressure(HTHP) geologic settings begins with the implementation of pre-drilling prediction techniques(PPTs). To improve the accuracy of geopressure prediction in HTHP hydrocarbon reservoirs offshore Hainan Island, we made a comprehensive summary of current PPTs to identify existing problems and challenges by analyzing the global distribution of HTHP hydrocarbon reservoirs, the research status of PPTs, and the geologic setting and its HTHP formation mechanism. Our research results indicate that the HTHP formation mechanism in the study area is caused by multiple factors, including rapid loading, diapir intrusions, hydrocarbon generation, and the thermal expansion of pore fluids. Due to this multi-factor interaction, a cloud of HTHP hydrocarbon reservoirs has developed in the Ying-Qiong Basin, but only traditional PPTs have been implemented, based on the assumption of conditions that do not conform to the actual geologic environment, e.g., Bellotti's law and Eaton's law. In this paper, we focus on these issues, identify some challenges and solutions, and call for further PPT research to address the drawbacks of previous works and meet the challenges associated with the deepwater technology gap. In this way, we hope to contribute to the improved accuracy of geopressure prediction prior to drilling and provide support for future HTHP drilling offshore Hainan Island.

Prediction of petroleum exploration risk and subterranean spatial distribution of hydrocarbon accumulations

Investigation of spatial distribution of oil and gas resource and accurate prediction of the geographic location of its undiscovered resource is significant for reducing exploration risk and improving exploration benefit.A new method for predicting spatial distribution of oil resource is discussed in this paper.It consists of prediction of risk probability in petroleum exploration and simulation of hydrocarbon abundance. Exploration risk probability is predicted by multivariate statistics,fuzzy mathematics and information processing techniques.A spatial attribute database for sample wells was set up and the Mahalanobis distance and Fuzzy value of given samples were obtained.Then,the Bayesian formula was used to calculate the hydrocarbon-bearing probability at the area of exploration wells.Finally,a hydrocarbon probability template is formed and used to forecast the probability of the unknown area. The hydrocarbon abundance is simulated based on Fourier integrals,frequency spectrum synthesis and fractal theory.Firstly,the fast Fourier transformation（FFT） is used to transform the known hydrocarbon abundance from the spatial domain to the frequency domain,then,frequency spectrum synthesis is used to produce the fractal frequency spectrum,and FFT is applied to get the phase information of hydrocarbon-bearing probability.Finally,the frequency spectrum simulation is used to calculate the renewed hydrocarbon abundance in the play. This method is used to predict the abundance and possible locations of the undiscovered petroleum accumulations in the Nanpu Sag of the Bohai Bay Basin,China.The prediction results for the well-explored onshore area of the northern Nanpu Sag agree well with the actual situations.For the less-explored offshore areas in the southern Nanpu Sag,the prediction results suggest high hydrocarbon abundance in Nanpu-1 and Nanpu-2,providing a useful guiding for future exploration.

Control of Facies and Potential on Jurassic Hydrocarbon Accumulation and Prediction of Favorable Targets in the Hinterland Region of the Junggar Basin

Exploration practices show that the Jurassic System in the hinterland region of the Junggar Basin has a low degree of exploration but huge potential, however the oil/gas accumulation rule is very complicated, and it is difficult to predict hydrocarbon-bearing properties. The research indicates that the oil and gas is controlled by structure facies belt and sedimentary system distribution macroscopically, and hydrocarbon-bearing properties of sand bodies are controlled by lithofacies and petrophysical facies microscopically. Controlled by ancient and current tectonic frameworks, most of the discovered oil and gas are distributed in the delta front sedimentary system of a palaeo-tectonic belt and an ancient slope belt. Subaqueous branch channels and estuary dams mainly with medium and fine sandstone are the main reservoirs and oil production layers, and sand bodies of high porosity and high permeability have good hydrocarbon-bearing properties; the facies controlling effect shows a reservoir controlling geologic model of relatively high porosity and permeability. The hydrocarbon distribution is also controlled by relatively low potential energy at the high points of local structure macroscopically, while most of the successful wells are distributed at the high points of local structure, and the hydrocarbon-bearing property is good at the place of relatively low potential energy; the hydrocarbon distribution is in close connection with faults, and the reservoirs near the fault in the region of relatively low pressure have good oil and gas shows; the distribution of lithologic reservoirs at the depression slope is controlled by the distribution of sand bodies at positions of relatively high porosity and permeability. The formation of the reservoir of the Jurassic in the Junggar Basin shows characteristics of favorable facies and low-potential coupling control, and among the currenffy discovered reservoirs and industrial hydrocarbon production wells, more than 90% are developed within the scope of facies- potential index FPI〉0.5, while the FPI and oil saturation of the discovered reservoir and unascertained traps have relatively good linear correlation. By establishing the relation model between hydrocarbon- bearing properties of traps and FPI, totally 43 favorable targets are predicted in four main target series of strata and mainly distributed in the Badaowan Formation and the Sangonghe Formation, and the most favorable targets include the north and east of the Shinan Sag, the middle and south of the Mobei Uplift, Cai-35 well area of the Cainan Oilfield, and North-74 well area of the Zhangbei fault-fold zone.

Alteration and Reformation of Hydrocarbon Reservoirs and Prediction of Remaining Potential Resources in Superimposed Basins

Complex hydrocarbon reservoirs developed widely in the superimposed basins of China formed from multiple structural alterations, reformation and destruction of hydrocarbon reservoirs formed at early stages. They are characterized currently by trap adjustment, component variation, phase conversion, and scale reformation. This is significant for guiding current hydrocarbon exploration by revealing evolution mechanisms after hydrocarbon reservoir formation and for predicting remaining potential resources. Based on the analysis of a number of complex hydrocarbon reservoirs, there are four geologic features controlling the degree of destruction of hydrocarbon reservoirs formed at early stages： tectonic event intensity, frequency, time and caprock sealing for oil and gas during tectonic evolution. Research shows that the larger the tectonic event intensity, the more frequent the tectonic event, the later the last tectonic event, the weaker the caprock sealing for oil and gas, and the greater the volume of destroyed hydrocarbons in the early stages. Based on research on the main controlling factors of hydrocarbon reservoir destruction mechanisms, a geological model of tectonic superimposition and a mathematical model evaluating potential remaining complex hydrocarbon reservoirs have been established. The predication method and technical procedures were applied in the Tazhong area of Tarim Basin, where four stages of hydrocarbon accumulation and three stages of hydrocarbon alteration occurred. Geohistorical hydrocarbon accumulation reached 3.184 billion tons, of which 1.271 billion tons were destroyed. The total volume of remaining resources available for exploration is -1.9 billion tons.

Generalized Pareto Distribution Model and Its Application to Hydrocarbon Resource Structure Prediction of the Huanghua Depression

The generalized Pareto distribution model is a kind of hydrocarbon pool size probability statistical method for resource assessment. By introducing the time variable, resource conversion rate and the geological variable, resource density, such model can describe not only different types of basins, but also any exploration samples at different phases of exploration, up to the parent population. It is a dynamic distribution model with profound geological significance and wide applicability. Its basic principle and the process of resource assessment are described in this paper. The petroleum accumulation system is an appropriate assessment unit for such method. The hydrocarbon resource structure of the Huanghua Depression in Bohai Bay Basin was predicted by using this model. The prediction results accord with the knowledge of exploration in the Huanghua Depression, and point out the remaining resources potential and structure of different petroleum accumulation systems, which are of great significance for guiding future exploration in the Huanghua Depression.

Control of facies and fluid potential on hydrocarbon accumulation and prediction of favorable Silurian targets in the Tazhong Uplift,Tarim Basin,China

Exploration practices show that the Silurian hydrocarbon accumulation in the Tazhong Uplift is extremely complicated.Our research indicates that the oil and gas accumulation is controlled by favorable facies and low fluid potential.At the macro level,hydrocarbon distribution in this uplift is controlled by structural zones and sedimentary systems.At the micro level,oil occurrences are dominated by lithofacies and petrophysical facies.The control of facies is embodied in high porosity and permeability controlling hydrocarbon accumulation.Besides,the macro oil and gas distribution in the uplift is also influenced by the relatively low fluid potential at local highs,where most successful wells are located.These wells are also closely related to the adjacent fractures.Therefore,the Silurian hydrocarbon accumulation mechanism in the Tazhong Uplift can be described as follows.Induced by structures,the deep and overpressured fluids migrated through faults into the sand bodies with relatively low potential and high porosity and permeability.The released overpressure expelled the oil and gas into the normal-pressured zones,and the hydrocarbon was preserved by the overlying caprock of poorly compacted Carboniferous and Permian mudstones.Such a mechanism reflects favorable facies and low potential controlling hydrocarbon accumulation.Based on the statistical analysis of the reservoirs and commercial wells in the uplift,a relationship between oil-bearing property in traps and the facies-potential index was established,and a prediction of two favorable targets was made.

Prediction of Infinite Dilution Activity Coefficients of Halogenated Hydrocarbons in Water

Geometrical optimization and electrostatic potential calculations have been performed for a series of halogenated hydrocarbons at the HF/Gen-6d level. A number of electrostatic potentials and the statistically based structural descriptors derived from these electrostatic potentials have been obtained. Multiple linear regression analysis and artificial neural network are employed simultaneously in this paper. The result shows that the parameters derived from electrostatic 2 potentials σtot^2, V s and ∑ Vs^＋, together with the molecular volume （Vine） can be used to express the quantitative structure-infinite dilution activity coefficients （γ^∞） relationship of halogenated hydrocarbons in water. The result also demonstrates that the model obtained by using BFGS quasiNewton neural network method has much better predictive capability than that from multiple linear regression. The goodness of the model has been validated through exploring the predictive power for the external test set. The model obtained via neural network may be applied to predict γ^∞ of other halogenated hydrocarbons not present in the data set.

Prediction study of hydrocarbon reservoir based on time-frequency domain electromagnetic technique taking Ili Basin as an example

The time-frequency domain electromagnetic(TFEM)sounding technique can directly detect oil and gas characteristics through anomalies in resistivity and polarizability.In recent years,it has made some breakthroughs in hydrocarbon detection.TFEM was applied to predict the petroliferous property of the Ili Basin.In accordance with the geological structure characteristics of the study area,a two-dimensional layered medium model was constructed and forward modeling was performed.We used the forward-modeling results to guide fi eld construction and ensure the quality of the fi eld data collection.We used the model inversion results to identify and distinguish the resolution of the geoelectric information and provide a reliable basis for data processing.On the basis of our results,key technologies such as 2D resistivity tomography imaging inversion and polarimetric constrained inversion were developed,and we obtained abundant geological and geophysical information.The characteristics of the TFEM anomalies of the hydrocarbon reservoirs in the Ili Basin were summarized through an analysis of the electrical logging data in the study area.Moreover,the oil-gas properties of the Permian and Triassic layers were predicted,and the next favorable exploration targets were optimized.

Geophysical prediction of organic matter abundance in source rocks based on geochemical analysis:A case study of southwestern Bozhong Sag,Bohai Sea,China

The Bozhong Sag is the largest petroliferous sag in the Bohai Bay Basin,and the source rocks of Paleogene Dongying and Shahejie Formations were buried deeply.Most of the drillings were located at the structural high,and there were few wells that met good quality source rocks,so it is difficult to evaluate the source rocks in the study area precisely by geochemical analysis only.Based on the Rock-Eval pyrolysis,total organic carbon(TOC)testing,the organic matter(OM)abundance of Paleogene source rocks in the southwestern Bozhong Sag were evaluated,including the lower of second member of Dongying Formation(E_(3)d2L),the third member of Dongying Formation(E_(3)d_(3)),the first and second members of Shahejie Formation(E_(2)s_(1+2)),the third member of Shahejie Formation(E_(2)s_(3)).The results indicate that the E_(2)s_(1+2)and E_(2)s_(3)have better hydrocarbon generative potentials with the highest OM abundance,the E_(3)d_(3)are of the second good quality,and the E_(3)d2L have poor to fair hydrocarbon generative potential.Furthermore,the well logs were applied to predict TOC and residual hydrocarbon generation potential(S_(2))based on the sedimentary facies classification,usingΔlogR,generalizedΔlogR,logging multiple linear regression and BP neural network methods.The various methods were compared,and the BP neural network method have relatively better prediction accuracy.Based on the pre-stack simultaneous inversion(P-wave impedance,P-wave velocity and density inversion results)and the post-stack seismic attributes,the three-dimensional(3D)seismic prediction of TOC and S_(2)was carried out.The results show that the seismic near well prediction results of TOC and S_(2)based on seismic multi-attributes analysis correspond well with the results of well logging methods,and the plane prediction results are identical with the sedimentary facies map in the study area.The TOC and S_(2)values of E_(2)s_(1+2)and E_(2)s_(3)are higher than those in E_(3)d_(3)and E_(3)d_(2)L,basically consistent with the geochemical analysis results.This method makes up the deficiency of geochemical methods,establishing the connection between geophysical information and geochemical data,and it is helpful to the 3D quantitative prediction and the evaluation of high-quality source rocks in the areas where the drillings are limited.

Hydrocarbon accumulation and orderly distribution of whole petroleum system in marine carbonate rocks of Sichuan Basin,SW China

Based on the situation and progress of marine oil/gas exploration in the Sichuan Basin,SW China,the whole petroleum system is divided for marine carbonate rocks of the basin according to the combinations of hydrocarbon accumulation elements,especially the source rock.The hydrocarbon accumulation characteristics of each whole petroleum system are analyzed,the patterns of integrated conventional and unconventional hydrocarbon accumulation are summarized,and the favorable exploration targets are proposed.Under the control of multiple extensional-convergent tectonic cycles,the marine carbonate rocks of the Sichuan Basin contain three sets of regional source rocks and three sets of regional cap rocks,and can be divided into the Cambrian,Silurian and Permian whole petroleum systems.These whole petroleum systems present mainly independent hydrocarbon accumulation,containing natural gas of affinity individually.Locally,large fault zones run through multiple whole petroleum systems,forming a fault-controlled complex whole petroleum system.The hydrocarbon accumulation sequence of continental shelf facies shale gas accumulation,marginal platform facies-controlled gas reservoirs,and intra-platform fault-and facies-controlled gas reservoirs is common in the whole petroleum system,with a stereoscopic accumulation and orderly distribution pattern.High-quality source rock is fundamental to the formation of large gas fields,and natural gas in a whole petroleum system is generally enriched near and within the source rocks.The development and maintenance of large-scale reservoirs are essential for natural gas enrichment,multiple sources,oil and gas transformation,and dynamic adjustment are the characteristics of marine petroleum accumulation,and good preservation conditions are critical to natural gas accumulation.Large-scale marginal-platform reef-bank facies zones,deep shale gas,and large-scale lithological complexes related to source-connected faults are future marine hydrocarbon exploration targets in the Sichuan Basin.

Geological Model of Pre-Jurassic Heterogeneous Basement and Hydrocarbon Productivity Prediction of “Oil-and-Gas Bearing Contact Zone Horizon” Between Paleozoic and Mesozoic Deposits of Ostaninskoye and Severoostaninskoye Oil-and-Gas Fields(Western Siberi

This work is devoted to the analysis of the formation conditions and geologic model of Paleozoic basement rocks of a number of oil-and-gas fields, located in Tomsk region(South of West-Siberian Oil-and-Gas Province,Russia).The research is based on integrated data interpretation of seismic exploration, well logging and deep drilling.The study is at the interfaces between exploration geophysics

An innovative classification system for ranking the biological effects of marine aromatic hydrocarbons based on fish embryotoxicity

Petroleum hydrocarbon pollution is a global concern,particularly in coastal environments.Polycyclic aromatic hydrocarbons(PAHs) are regarded as the most toxic components of petroleum hydrocarbons.In this study,the biomonitoring and ranking effects of petroleum hydrocarbons and PAHs on the marine fish model Oryzias melastigma embryos were determined in the Jiulong River Estuary(JRE) and its adjacent waters in China.The results showed that the levels of petroleum hydrocarbons from almost all sites met the primary standard for marine seawater quality,and the concentrations of the 16 priority PAHs in the surface seawater were lower compared with those in other coastal areas worldwide.A new fish expert system based on the embryotoxicity of O.melastigma(OME-FES) was developed and applied in the field to evaluate the biological effects of petroleum hydrocarbons and PAHs.The selected physiological index and molecular indicators in OME-FES were appropriate biomarkers for indicating the harmful effects of petroleum hydrocarbons and PAHs.The outcome of OME-FES revealed that the biological effect levels of the sampling sites ranged from level Ⅰ(no stress) to level Ⅲ(medium stress),which is further corroborated by the findings of nested analysis of variance(ANOVA) models.Our results suggest that the OME-FES is an effective tool for evaluating and ranking the biological effects of marine petroleum hydrocarbons and PAHs.This method may also be applied to evaluate other marine pollutants based on its framework.

Classifying rockburst with confidence:A novel conformal prediction approach

The scientific community recognizes the seriousness of rockbursts and the need for effective mitigation measures.The literature reports various successful applications of machine learning(ML)models for rockburst assessment;however,a significant question remains unanswered:How reliable are these models,and at what confidence level are classifications made?Typically,ML models output single rockburst grade even in the face of intricate and out-of-distribution samples,without any associated confidence value.Given the susceptibility of ML models to errors,it becomes imperative to quantify their uncertainty to prevent consequential failures.To address this issue,we propose a conformal prediction(CP)framework built on traditional ML models(extreme gradient boosting and random forest)to generate valid classifications of rockburst while producing a measure of confidence for its output.The proposed framework guarantees marginal coverage and,in most cases,conditional coverage on the test dataset.The CP was evaluated on a rockburst case in the Sanshandao Gold Mine in China,where it achieved high coverage and efficiency at applicable confidence levels.Significantly,the CP identified several“confident”classifications from the traditional ML model as unreliable,necessitating expert verification for informed decision-making.The proposed framework improves the reliability and accuracy of rockburst assessments,with the potential to bolster user confidence.

Hydrocarbon accumulation in deep ancient carbonate-evaporite assemblages

The Ediacaran–Ordovician strata within three major marine basins(Tarim,Sichuan,and Ordos)in China are analyzed.Based on previous studies focusing on the characteristics of the Neoproterozoic–Cambrian strata within the three major basins(East Siberian,Oman,and Officer in Australia)overseas,the carbonate–evaporite assemblages in the target interval are divided into three types:intercalated carbonate and gypsum salt,interbedded carbonate and gypsum salt,and coexisted carbonate,gypsum salt and clastic rock.Moreover,the concept and definition of the carbonate-evaporite assemblage are clarified.The results indicate that the oil and gas in the carbonate-evaporite assemblage are originated from two types of source rocks:shale and argillaceous carbonate,and confirmed the capability of gypsum salt in the saline environment to drive the source rock hydrocarbon generation.The dolomite reservoirs are classified in two types:gypseous dolomite flat,and grain shoal&microbial mound.This study clarifies that the penecontemporaneous or epigenic leaching of atmospheric fresh water mainly controlled the large-scale development of reservoirs.Afterwards,burial dissolution transformed and reworked the reservoirs.The hydrocarbon accumulation in carbonate-evaporite assemblage can be categorized into eight sub-models under three models(sub-evaporite hydrocarbon accumulation,supra-evaporite hydrocarbon accumulation,and inter-evaporite hydrocarbon accumulation).As a result,the Cambrian strata in the Tazhong Uplift North Slope,Maigaiti Slope and Mazatag Front Uplift Zone of the Tarim Basin,the Cambrian strata in the eastern-southern area of the Sichuan Basin,and the inter-evaporite Ma-4 Member of Ordovician in the Ordos Basin,China,are defined as favorable targets for future exploration.

Geochemical identification of a source rock affected by migrated hydrocarbons and its geological significance:Fengcheng Formation,southern Mahu Sag,Junggar Basin,NW China

The Fengcheng Formation is a crucial source rock and the primary reservoir for oil accumulation in the Mahu Sag.Crude oils are distributed throughout the Fengcheng Formation,ranging from the edge to the interior of the sag in the southern Mahu Sag.These crude oils originate from in-situ source rocks in shallowly buried areas and the inner deep sag.During migration,the crude oil from the inner deep sag affects the source rocks close to carrier beds,leading to changes in the organic geochemical characteristics of the source rocks.These changes might alter source rock evaluations and oil-source correlation.Based on data such as total organic carbon(TOC),Rock-Eval pyrolysis of source rocks,and gas chromatography-mass spectrometry(GC-MS)of the saturated fraction,and considering the geological characteristics of the study area,we define the identification characteristics of source rock affected by migrated hydrocarbons and establish the various patterns of influence that migrated hydrocarbons have on the source rock of the Fengcheng Formation in the southern Mahu Sag.The source rocks of the Fengcheng Formation are mostly fair to good,containing mainly Type II organic matter and being thermally mature enough to generate oil.Source rocks affected by migrated hydrocarbons exhibit relatively high hydrocarbon contents(S1/TOC>110 mg HC/g TOC,Extract/TOC>30%,HC:hydrocarbon),relatively low Rock-Eval Tmax values,and relatively high tricyclic terpane contents with a descending and mountain-shaped distribution.Furthermore,biomarker composition parameters indicate a higher thermal maturity than in-situ source rocks.Through a comparison of the extract biomarker fingerprints of adjacent reservoirs and mudstones in different boreholes,three types of influence patterns of migrated hydrocarbons are identified:the edge-influence of thin sandstone-thick mudstone,the mixed-influence of sandstone-mudstone interbedded,and the full-influence of thick sandstone-thin mudstone.This finding reminds us that the influence of migrated hydrocarbons must be considered when evaluating source rocks and conducting oil-source correlation.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.