A log-based method for fine-scale evaluation of lithofacies and its applications to the Gulong shale in the Songliao Basin,Northeast China

The Gulong shale demonstrates high clay content and pronounced thin laminations,with limited vertical variability in log curves,complicating lithofacies classification.To comprehend the distribution and compositional features of lithofacies in the Gulong shale for optimal sweet spot selection and reservoir stimulation,this study introduced a lithofacies classification scheme and a log-based lithofacies evaluation method.Specifically,theΔlgR method was utilized for accurately determining the total organic carbon(TOC)content;a multi-mineral model based on element-to-mineral content conversion coefficients was developed to enhance mineral composition prediction accuracy,and the microresistivity curve variations derived from formation micro-image(FMI)log were used to compute lamination density,offering insights into sedimentary structures.Using this method,integrating TOC content,sedimentary structures,and mineral compositions,the Qingshankou Formation is classified into four lithofacies and 12 sublithofacies,displaying 90.6%accuracy compared to core description outcomes.The classification results reveal that the northern portion of the study area exhibits more prevalent fissile felsic shales,siltstone interlayers,shell limestones,and dolomites.Vertically,the upper section primarily exhibits organic-rich felsic shale and siltstone interlayers,the middle part is characterized by moderate organic quartz-feldspathic shale and siltstone/carbonate interlayers,and the lower section predominantly features organic-rich fissile felsic/clayey felsic shales.Analyzing various sublithofacies in relation to seven petrophysical parameters,oil test production,and fracturing operation conditions indicates that the organic-rich felsic shales in the upper section and the organic-rich/clayey felsic shales in the lower section possess superior physical properties and oil content,contributing to smoother fracturing operation and enhanced production,thus emerging as dominant sublithofacies.Conversely,thin interlayers such as siltstones and limestones,while producing oil,demonstrate higher brittleness and pose great fracturing operation challenges.The methodology and insights in this study will provide a valuable guide for sweet spot identification and horizontal well-based exploitation of the Gulong shale.

Hydrocarbon Potential of the Triassic-Jurassic Sediments in Southeast Sulawesi, Indonesia, Based on Lithofacies and Geochemical Analysis

Triassic-Jurassic carbonates widely distributed in Eastern Indonesia are believed as oils source rock. The Mesozoic Tokala Formation exhibit source rock potential, as evidenced by high contents of organic matter. Recent exploration has been conducted in southeastern Sulawesi, targeting the Mesozoic intervals. Therefore, in this study, we attempted to determine source rock potential of Tokala Formation outcropped in southeastern Sulawesi area and its capability to generate hydrocarbon. Five distinct lithofacies were delineated, emphasizing lithological and mineralogical features: foraminifera wackestone (FW), lime mudstone (LM), massive bioturbated calcareous-argillaceous shale (MBCAS), weakly laminated argillaceous-calcareous shale (WLACS), and strongly laminated calcareous-argillaceous shale (SLCAS). Subsequent analyses showed that carbonate-rich samples (FW and LM facies, >50% CaO) had poor source rock potential. Conversely, shale facies with moderate carbonate content (WLACS, MBCAS, and SLCAS, 15% - 50% CaO) had good to excellent source rock characteristics, qualifying them as preferable source rock. In addition, levels of SiO2 and Al2O3 should not be neglected, as these constituents play important roles in clay mineral adsorption. Laminated shale facies with moderate CaO content tended to be more promising as source rock than bioturbated facies. The shale facies of Tokala Formation indicate prospective source rock horizon.

A deep kernel method for lithofacies identification using conventional well logs

How to fit a properly nonlinear classification model from conventional well logs to lithofacies is a key problem for machine learning methods.Kernel methods(e.g.,KFD,SVM,MSVM)are effective attempts to solve this issue due to abilities of handling nonlinear features by kernel functions.Deep mining of log features indicating lithofacies still needs to be improved for kernel methods.Hence,this work employs deep neural networks to enhance the kernel principal component analysis(KPCA)method and proposes a deep kernel method(DKM)for lithofacies identification using well logs.DKM includes a feature extractor and a classifier.The feature extractor consists of a series of KPCA models arranged according to residual network structure.A gradient-free optimization method is introduced to automatically optimize parameters and structure in DKM,which can avoid complex tuning of parameters in models.To test the validation of the proposed DKM for lithofacies identification,an open-sourced dataset with seven con-ventional logs(GR,CAL,AC,DEN,CNL,LLD,and LLS)and lithofacies labels from the Daniudi Gas Field in China is used.There are eight lithofacies,namely clastic rocks(pebbly,coarse,medium,and fine sand-stone,siltstone,mudstone),coal,and carbonate rocks.The comparisons between DKM and three commonly used kernel methods(KFD,SVM,MSVM)show that(1)DKM(85.7%)outperforms SVM(77%),KFD(79.5%),and MSVM(82.8%)in accuracy of lithofacies identification;(2)DKM is about twice faster than the multi-kernel method(MSVM)with good accuracy.The blind well test in Well D13 indicates that compared with the other three methods DKM improves about 24%in accuracy,35%in precision,41%in recall,and 40%in F1 score,respectively.In general,DKM is an effective method for complex lithofacies identification.This work also discussed the optimal structure and classifier for DKM.Experimental re-sults show that(m_(1),m_(2),O)is the optimal model structure and linear svM is the optimal classifier.(m_(1),m_(2),O)means there are m KPCAs,and then m2 residual units.A workflow to determine an optimal classifier in DKM for lithofacies identification is proposed,too.

How to improve machine learning models for lithofacies identification by practical and novel ensemble strategy and principles

Typically, relationship between well logs and lithofacies is complex, which leads to low accuracy of lithofacies identification. Machine learning (ML) methods are often applied to identify lithofacies using logs labelled by rock cores. However, these methods have accuracy limits to some extent. To further improve their accuracies, practical and novel ensemble learning strategy and principles are proposed in this work, which allows geologists not familiar with ML to establish a good ML lithofacies identification model and help geologists familiar with ML further improve accuracy of lithofacies identification. The ensemble learning strategy combines ML methods as sub-classifiers to generate a comprehensive lithofacies identification model, which aims to reduce the variance errors in prediction. Each sub-classifier is trained by randomly sampled labelled data with random features. The novelty of this work lies in the ensemble principles making sub-classifiers just overfitting by algorithm parameter setting and sub-dataset sampling. The principles can help reduce the bias errors in the prediction. Two issues are discussed, videlicet (1) whether only a relatively simple single-classifier method can be as sub-classifiers and how to select proper ML methods as sub-classifiers;(2) whether different kinds of ML methods can be combined as sub-classifiers. If yes, how to determine a proper combination. In order to test the effectiveness of the ensemble strategy and principles for lithofacies identification, different kinds of machine learning algorithms are selected as sub-classifiers, including regular classifiers (LDA, NB, KNN, ID3 tree and CART), kernel method (SVM), and ensemble learning algorithms (RF, AdaBoost, XGBoost and LightGBM). In this work, the experiments used a published dataset of lithofacies from Daniudi gas field (DGF) in Ordes Basin, China. Based on a series of comparisons between ML algorithms and their corresponding ensemble models using the ensemble strategy and principles, conclusions are drawn: (1) not only decision tree but also other single-classifiers and ensemble-learning-classifiers can be used as sub-classifiers of homogeneous ensemble learning and the ensemble can improve the accuracy of the original classifiers;(2) the ensemble principles for the introduced homogeneous and heterogeneous ensemble strategy are effective in promoting ML in lithofacies identification;(3) in practice, heterogeneous ensemble is more suitable for building a more powerful lithofacies identification model, though it is complex.

High-resolution coupling of stratigraphic'sweet-spot'lithofacies and petrophysical properties:A multiscale study of Ordovician Goldwyer Formation,Western Australia

The identification of stratigraphic'sweet-spot'interval is significant in oil and gas formation evaluation.However,formation evaluation in macroscopic-scale merely provides low resolution and limited infor-mation,thus may lead to uncertainties in resource estimation.To accurately identify the'sweet-spot'intervals amongst heterogeneous lithofacies,we conducted a very high-resolution and quantitative analysis from in-situ macroscopic scale to laboratory microscopic scale on the Goldwyer formation of Canning Basin,Western Australia.The comprehensive advanced well logging and slim-compact micro imager(SCMI)technologies were synthetically applied in couple with the laboratory nanoscaled ex-periments.The results unveiled an extraordinarily large lithofacies heterogeneity between different rock intervals,with distinguished features shown in Goldwyer Ⅰ,Ⅱ,and Ⅲ members.The most favorable lithofacies is recognized as the laminated argillaceous thermally-matured organic matter(OM)-rich mudstone,which is widely developed in Goldwyer Ⅲ as the major attributor to'sweet-spot'intervals.Goldwyer Ⅱ is exclusively characterized by thick mudstone intervals(94.4%),interbedded with thin calcareous mudstones(5.5%),corresponding to a depositional environment of low-energy distal section of the outer ramp settings.Microscopically,the most favorable lithofacies in'sweet-spot'intervals develop numerous OM-/mineral nanopores for hydrocarbon storage.Illite-rich lithofacies develops abundant inter-particle pores from 2 to 17 nm that mainly contribute to pore volume for free gas storage capacity.OM-rich lithofacies with higher maturity have OM-pores with good connectivity,bearing large specific surface area that is beneficial for adsorbed gas capacity.

Depositional Environment and Lithofacies Analyses of Eocene Lacustrine Shale in the Bohai Bay Basin:Insights from Mineralogy and Elemental Geochemistry

The effect of various depositional parameters including paleoclimate,paleosalinity and provenance,on the depositional mechanism of lacustrine shale is very important in reconstructing the depositional environment.The classification of shale lithofacies and the interpretation of shale depositional environment are key features used in shale oil and gas exploration and development activity.The lower 3rd member of the Eocene Shahejie Formation(Es_(3)^(x)shale)was selected for this study,as one of the main prospective intervals for shale oil exploration and development in the intracratonic Bohai Bay Basin.Mineralogically,it is composed of quartz(avg.9.6%),calcite(avg.58.5%),dolomite(avg.7%),pyrite(avg.3.3%)and clay minerals(avg.20%).An advanced methodology(thin-section petrography,total organic carbon and total organic sulfur contents analysis,X-ray diffraction(XRD),X-ray fluorescence(XRF),field-emission scanning electron microscopy(FE-SEM))was adopted to establish shale lithofacies and to interpret the depositional environment in the lacustrine basin.Six different types of lithofacies were recognized,based on mineral composition,total organic carbon(TOC)content and sedimentary structures.Various inorganic geochemical proxies(Rb/Sr,Ca/(Ca+Fe),Ti/Al,Al/Ca,Al/Ti,Zr/Rb)have been used to interpret and screen variations in depositional environmental parameters during the deposition of the Es_(3)^(x)shale.The experimental results indicate that the environment during the deposition of the Es_(3)^(x)shale was warm and humid with heightened salinities,moderate to limited detrital input,higher paleohydrodynamic settings and strong oxygen deficient(reducing)conditions.A comprehensive depositional model of the lacustrine shale was developed.The interpretations deduced from this research work are expected to not only expand the knowledge of shale lithofacies classification for lacustrine fine-grained rocks,but can also offer a theoretical foundation for lacustrine shale oil exploration and development.

Favorable lithofacies and pore characteristics of the Permian Longtan Formation shale in the southern Sichuan Basin

The marine–continental transitional shale (MCTS) reservoirs of the Longtan Formation (LTF) are widely distributed in the Sichuan Basin. However, the LTF shale exhibits considerable variations in mineral composition and pore characteristics, which makes identifying the 'sweet spot'a challenging task. To address this issue, 10 samples from four typical shale gas wells in the LTF in the southern Sichuan Basin were selected and analyzed for total organic carbon (TOC) content, whole-rock composition using X-ray diffraction (XRD), low-pressure gas adsorption, and high-pressure mercury intrusion. The lithofacies distribution and pore structure of the MCTS were studied to determine the pore structural characteristics and the primary factors influencing pore formation in different types of shale lithofacies in the LTF. The lithofacies of the LTF shale in the study area can be classified into three categories: siliceous clay shale, clay shale and mixed shale. Mineral content has a significant impact on the pore characteristics, while TOC content has a minor effect on the pore volume and specific surface area of micropores and mesopores. It can be inferred that the mesopores in the MCTS are mainly related to clay mineral pores, and mineral dissolution and TOC content are not the primary factors contributing to pore formation.

Lithofacies paleogeography mapping and reservoir prediction in tight sandstone strata: A case study from central Sichuan Basin, China

Sand-rich tight sandstone reservoirs are potential areas for oil and gas exploration. However, the high ratio of sandstone thickness to that of the strata in the formation poses many challenges and uncertainties to traditional lithofacies paleogeography mapping. Therefore, the prediction of reservoir sweet spots has remained problematic in the field of petroleum exploration. This study provides new insight into resolving this problem, based on the analyses of depositional characteristics of a typical modern sand-rich formation in a shallow braided river delta of the central Sichuan Basin, China. The varieties of sand-rich strata in the braided river delta environment include primary braided channels,secondary distributary channels and the distribution of sediments is controlled by the successive superposed strata deposited in paleogeomorphic valleys. The primary distributary channels have stronger hydrodynamic forces with higher proportions of coarse sand deposits than the secondary distributary channels. Therefore, lithofacies paleogeography mapping is controlled by the geomorphology, valley locations, and the migration of channels. We reconstructed the paleogeomorphology and valley systems that existed prior to the deposition of the Xujiahe Formation. Following this, rock-electro identification model for coarse skeletal sand bodies was constructed based on coring data. The results suggest that skeletal sand bodies in primary distributary channels occur mainly in the valleys and low-lying areas,whereas secondary distributary channels and fine deposits generally occur in the highland areas. The thickness distribution of skeletal sand bodies and lithofacies paleogeography map indicate a positive correlation in primary distributary channels and reservoir thickness. A significant correlation exists between different sedimentary facies and petrophysical properties. In addition, the degree of reservoir development in different sedimentary facies indicates that the mapping method reliably predicts the distribution of sweet spots. The application and understanding of the mapping method provide a reference for exploring tight sandstone reservoirs on a regional basis.

Multi-resolution graph-based clustering analysis for lithofacies identifi cation from well log data: Case study of intraplatform bank gas fi elds, Amu Darya Basin

In this study, we used the multi-resolution graph-based clustering （MRGC） method for determining the electrofacies （EF） and lithofacies （LF） from well log data obtained from the intraplatform bank gas fields located in the Amu Darya Basin. The MRGC could automatically determine the optimal number of clusters without prior knowledge about the structure or cluster numbers of the analyzed data set and allowed the users to control the level of detail actually needed to define the EF. Based on the LF identification and successful EF calibration using core data, an MRGC EF partition model including five clusters and a quantitative LF interpretation chart were constructed. The EF clusters 1 to 5 were interpreted as lagoon, anhydrite flat, interbank, low-energy bank, and high-energy bank, and the coincidence rate in the cored interval could reach 85%. We concluded that the MRGC could be accurately applied to predict the LF in non-cored but logged wells. Therefore, continuous EF clusters were partitioned and corresponding LF were characteristics ＆different LF were analyzed interpreted, and the distribution and petrophysical in the framework of sequence stratigraphy.

Lower Es3 in Zhanhua Sag, Jiyang Depression： a case study for lithofacies classification in lacustrine mud shale

Oil and gas exploration in lacustrine mud shale has focused on laminated calcareous lithofacies rich in type Ⅰ or type Ⅱ1 organic matter, taking into account the mineralogy and bedding structure, and type and abundance of organic matter. Using the lower third member of the Shahejie Formation, Zhanhua Sag, Jiyang Depression as the target lithology, we applied core description, thin section observations, electron microscopy imaging, nuclear magnetic resonance, and fullbore formation microimager （FMI） to study the mud shale lithofacies and features. First, the lithofacies were classified by considering the bedding structure, lithology, and organic matter and then a lithofacies classification scheme of lacustrine mud shale was proposed. Second, we used optimal filtering of logging data to distinguish the lithologies. Because the fractals of logging data are good indicators of the bedding structure, gamma-ray radiation was used to optimize the structural identification. Total organic carbon content （TOC） and pyrolyzed hydrocarbons （S2） were calculated from the logging data, and the hydrogen index （HI） was obtained to identify the organic matter type of the different strata （HI vs Tmax）. Finally, a method for shale lithofacies identification based on logging data is proposed for exploring mud shale reservoirs and sweet spots from continuous wellbore profiles.

Lithofacies identi cation using support vector machine based on local deep multi-kernel learning

Lithofacies identification is a crucial work in reservoir characterization and modeling.The vast inter-well area can be supplemented by facies identification of seismic data.However,the relationship between lithofacies and seismic information that is affected by many factors is complicated.Machine learning has received extensive attention in recent years,among which support vector machine(SVM) is a potential method for lithofacies classification.Lithofacies classification involves identifying various types of lithofacies and is generally a nonlinear problem,which needs to be solved by means of the kernel function.Multi-kernel learning SVM is one of the main tools for solving the nonlinear problem about multi-classification.However,it is very difficult to determine the kernel function and the parameters,which is restricted by human factors.Besides,its computational efficiency is low.A lithofacies classification method based on local deep multi-kernel learning support vector machine(LDMKL-SVM) that can consider low-dimensional global features and high-dimensional local features is developed.The method can automatically learn parameters of kernel function and SVM to build a relationship between lithofacies and seismic elastic information.The calculation speed will be expedited at no cost with respect to discriminant accuracy for multi-class lithofacies identification.Both the model data test results and the field data application results certify advantages of the method.This contribution offers an effective method for lithofacies recognition and reservoir prediction by using SVM.

Favorable lithofacies types and genesis of marine- continental transitional black shale: A case study of Permian Shanxi Formation in the eastern margin of Ordos Basin, NW China

Based on core description,thin section identification,X-ray diffraction analysis,scanning electron microscopy,low-temperature gas adsorption and high-pressure mercury intrusion porosimetry,the shale lithofacies of Shan23 sub-member of Permian Shanxi Formation in the east margin of Ordos Basin was systematically analyzed in this study.The Shan23 sub-member has six lithofacies,namely,low TOC clay shale(C-L),low TOC siliceous shale(S-L),medium TOC siliceous shale(S-M),medium TOC hybrid shale(M-M),high TOC siliceous shale(S-H),and high TOC clay shale(C-H).Among them,S-H is the best lithofacies,S-M and M-M are the second best.The C-L and C-H lithofacies,mainly found in the upper part of Shan23 sub-member,generally developed in tide-dominated delta facies;the S-L,S-M,S-H and M-M shales occurring in the lower part of Shan23 sub-member developed in tide-dominated estuarine bay facies.The S-H,S-M and M-M shales have good pore struc-ture and largely organic matter pores and mineral interparticle pores,including interlayer pore in clay minerals,pyrite inter-crystalline pore,and mineral dissolution pore.C-L and S-L shales have mainly mineral interparticle pores and clay mineral in-terlayer pores,and a small amount of organic matter pores,showing poorer pore structure.The C-H shale has organic mi-cro-pores and a small number of interlayer fissures of clay minerals,showing good micro-pore structure,and poor meso-pore and macro-pore structure.The formation of favorable lithofacies is jointly controlled by depositional environment and diagen-esis.Shallow bay-lagoon depositional environment is conducive to the formation of type II2 kerogen which can produce a large number of organic cellular pores.Besides,the rich biogenic silica is conducive to the preservation of primary pores and en-hances the fracability of the shale reservoir.

Shale Lithofacies and Sedimentary Environment of the Third Member,Shahejie Formation,Zhanhua Sag,Eastern China

Researches into shale lithofacies,their sedimentary environments and relationship benefit understanding both of sedimentary cycle division and unconventional hydrocarbon exploration in lacustrine basins.Based on a 100~300-m-thick dark shale,mudstone and limestone encountered in the lower third member of the Eocene Shahejie Formation(Es3l member)in Zhanhua Sag,Bohai Bay Basin,eastern China,routine core analysis,thin sectioning,scanning electron microscopy(SEM),mineralogical and geochemical measurements were used to understand detailed facies characterization and paleoclimate in the member.This Es3l shale sediment includes three sedimentary cycles(C3,C2 and C1),from bottom to top,with complex sedimentary characters and spatial distribution.In terms of the composition,texture,bedding and thickness,six lithofacies are recognized in this succession.Some geochemical parameters,such as trace elements(Sr/Ba,Na/Al,V/Ni,V/(V+Ni),U/Th),carbon and oxygen isotopes(δ^(18)O,δ^(13)C),and total organic carbon content(TOC)indicate that the shales were deposited in a deep to semi-deep lake,with the water column being salty,stratified,enclosed and reductive.During cycles C3 and C2 of the middle-lower sections,the climate was arid,and the water was salty and stratified.Laminated and laminar mudstone-limestone was deposited with moderate organic matter(average TOC 1.8%)and good reservoir quality(average porosity 6.5%),which can be regarded as favorable reservoir.During the C1 cycle,a large amount of organic matter was input from outside the basin and this led to high productivity with a more humid climate.Massive calcareous mudstone was deposited,and this is characterized by high TOC(average 3.6%)and moderate porosity(average 4%),and provides favorable source rocks.

Lithofacies and Pore Structure of Fine-grained Sedimentary Rocks of Qing-1 Member of Cretaceous in the Southern Songliao Basin

Fine-grained sedimentary rocks often contain hydrocarbon and mineral resources.Compared with coarse-grained sedimentary rocks,fine-grained sedimentary rocks are less studied.To elucidate the lithofacies and pore structure of lacustrine fine-grained rocks,the 340.6 m continuous core of Cretaceous Qing-1 Member from five wells in the southern central depression of the Songliao Basin was analyzed using X-ray diffraction,Rock-Eval pyrolysis,low-temperature nitrogen adsorption,high-pressure mercury injection,argon ion polishing-field emission scanning electron microscopy,and laser scanning confocal microscopy.Based on mineral compositions,organic matter abundance and sedimentary structure,lacustrine fine-grained rocks in the study area were divided into ten lithofacies,with their spatial distributions mainly influenced by tectonic cycle,climate cycle and provenance.Furthermore,pore structure characteristics of different lithofacies are summarized.(1)The siliceous mudstone lithofacies with low TOC content and the laminated/layered claybearing siliceous mudstone lithofacies with medium TOC content have the highest proportion of first-class pores(diameter>100 nm),making it the most favourable lithofacies for the accumulation of shale oil and shale gas.(2)The massive claybearing siliceous mudstone lithofacies with low TOC content has the highest proportion of second-class pores(diameter ranges from 10 to 100 nm),making it a favourable lithofacies for the enrichment of shale gas.(3)The massive clay-bearing siliceous mudstone lithofacies with high TOC content has the highest proportion of third-class pores(diameter<10 nm),making it intermediate in gas storage and flow.Laser confocal oil analysis shows that the heavy component of oil is mainly distributed in the clay lamina,while the light part with higher mobility is mainly concentrated in the silty lamina.

Oil-gas reservoir lithofacies stochastic modeling based on one- to three-dimensional Markov chains

Stochastic modeling techniques have been widely applied to oil-gas reservoir lithofacies. Markov chain simulation~ however~ is still under development~ mainly because of the difficulties in reasonably defining conditional probabilities for multi-dimensional Markov chains and determining transition probabilities for horizontal strike and dip directions. The aim of this work is to solve these problems. Firstly~ the calculation formulae of conditional probabilities for multi-dimensional Markov chain models are proposed under the full independence and conditional independence assumptions. It is noted that multi-dimensional Markov models based on the conditional independence assumption are reasonable because these models avoid the small-class underestimation problem. Then~ the methods for determining transition probabilities are given. The vertical transition probabilities are obtained by computing the transition frequencies from drilling data~ while the horizontal transition probabilities are estimated by using well data and the elongation ratios according to Walther＇s law. Finally~ these models are used to simulate the reservoir lithofacies distribution of Tahe oilfield in China. The results show that the conditional independence method performs better than the full independence counterpart in maintaining the true percentage composition and reproducing lithofacies spatial features.

Lithofacies Characters and Significance of the Submarine Fan of the Liufengguan Group in Qinling

Field investigation and laboratory research on flysch of the Liufengguan Group in Qinling indicate the following： （1） Sandstone of the Liufengguan Group is categorized as feldspathic lithic graywacke with a minor amount of lithic graywacke in the QFR triangular diagram. Grain size〈0.3 mm. Bedding plane structures such as groove casts and suspected flute casts can be found at the bottom of the sandstone. It is inferred that currents may have come from the southeast during deposition. Bedding structures such as ripple marks, graded bedding, parallel bedding, small-scale cross bedding, climbing bedding, suspected convolute bedding, microlamination and sliding structures have also been observed, which are of indicative significance. It is thought that the Liufengguan Group has the sedimentary characteristics of bedding, bedding plane structures and lithologicai assemblages of deep-sea low-density turbidity current deposits. The vertical succession of the Bouma sequence in the inner fan subfacies zone is generally incomplete： the assemblage of Ta and Tabc is commonly seen; the succession of the middle fan subfacies zone is relatively complete; and divisions Te and Tb are common in the outer fan subfacies zone. （2） The flysh of the Liufengguan Group is a sequence of deep-sea argillaceous-arenaceous submarine fan deposits, in which the authors recognize the inner, middle and outer fan subfacies and also nine types of lithofacies： normal graded sandstone （A1）, medium- to thick-bedded, fine-grained sandstone （A2）, medium- to thick-bedded and massive siltstone （A3）, thin-bedded, fine-grained sandstone and mudstone （B1）, irregular interbeds of thinbedded, fine-grained sandstone and siltstone （B2）, thin-bedded, fine-grained sandstone （C1）, very thin-bedded, fine-grained sandstone （D1）, olistostromes （El） anddeep-sea mudstone （F）. The inner fan consists of four microfacies： natural levee （A1）, water channel （A2, A3） and olistostrome （El）; in the middle fan there also occur four microfacies, i.e., branch channel （B1）, branch channel （B2）, interdistributary bay （D1） and olistostrome. The outer fan is made up of the branch channel （C1） and sheet sand （D1） microfacies, which alternate vertically with sediments of deep-sea plain subfacies （F）. There occur fining- and thinning-upward channel deposits in the outer-fan subfacies zone of the submarine fan of the Liufengguan Group observed in this study. The quartz content of the graywacke of the deposits is all higher than 40% and may reach as high as 60%. Therefore, on the basis of the aforementioned features, this flysh should be formed in a passive continental-margin tectonic environment.

Sequence-lithofacies paleogeographic characteristics and petroleum geological significance of Lower Permian Qixia Stage in Sichuan Basin and its adjacent areas,SW China

Through the analysis of logging,field outcrops,cores and geochemical data,and based on the study of the relationships between sea level changes,sequence filling,paleo-geomorphy and lithofacies,the sequence lithofacies paleo-geography and evolution process of the Lower Permian Liangshan-Qixia Formation(Qixia Stage for short)in Sichuan Basin and its surrounding areas are restored.The Qixia Stage can be divided into three third-order sequences,in which SQ0,SQ1 and SQ2 are developed in the depression area,and SQ1 and SQ2 are only developed in other areas.The paleo-geomorphy reflected by the thickness of each sequence indicates that before the deposition of the Qixia Stage in the Early Permian,the areas surrounding the Sichuan Basin are characterized by“four uplifts and four depressions”,namely,four paleo-uplifts/paleo-lands of Kangdian,Hannan,Shennongjia and Xuefeng Mountain,and four depressions of Chengdu-Mianyang,Kangdian front,Jiangkou and Yichang;while the interior of the basin is characterized by“secondary uplifts,secondary depressions and alternating convex-concave”.SQ2 is the main shoal forming period of the Qixia Formation,and the high-energy mound shoal facies mainly developed in the highs of sedimentary paleo-geomorphy and the relative slope break zones.The distribution of dolomitic reservoirs(dolomite,limy dolomite and dolomitic limestone)has a good correlation with the sedimentary geomorphic highs and slope break zones.The favorable mound-shoal and dolomitic reservoirs are distributed around depressions at platform-margin and along highs and around sags in the basin.It is pointed out that the platform-margin area in western Sichuan Basin is still the key area for exploration at present;while areas around Chengdu-Mianyang depression and Guangwang secondary depression inside the platform and areas around sags in central Sichuan-southern Sichuan are favorable exploration areas for dolomitic reservoirs of the Qixia Formation in the next step.

Lithofacies paleogeography and exploration significance of Sinian Doushantuo depositional stage in the middle-upper Yangtze region, Sichuan Basin, SW China

In recent years, natural gas exploration in the Sinian Dengying Formation and shale gas exploration in Doushantuo Formation have made major breakthroughs in the Sichuan Basin and its adjacent areas. However, the sedimentary background of the Doushantuo Formation hasn't been studied systematically. The lithofacies paleogeographic pattern, sedimentary environment, sedimentary evolution and distribution of source rocks during the depositional stage of Doushantuo Formation were systematically analyzed by using a large amount of outcrop data, and a small amount of drilling and seismic data.(1) The sedimentary sequence and stratigraphic distribution of the Sinian Doushantuo Formation in the middle-upper Yangtze region were controlled by paleouplifts and marginal sags. The Doushantuo Formation in the paleouplift region was overlayed with thin thickness, including shore facies, mixed continental shelf facies and atypical carbonate platform facies. The marginal sag had complete strata and large thickness, and developed deep water shelf facies and restricted basin facies.(2) The Doushantuo Formation is divided into four members from bottom to top, and the sedimentary sequence is a complete sedimentary cycle of transgression–high position–regression. The first member is atypical carbonate gentle slope deposit in the early stage of the transgression, the second member is shore-mixed shelf deposit in the extensive transgression period, and the third member is atypical restricted–open sea platform deposit of the high position of the transgression.(3) The second member has organic-rich black shale developed with stable distribution and large thickness, which is an important source rock interval and major shale gas interval. The third member is characterized by microbial carbonate rock and has good storage conditions which is conducive to the accumulation of natural gas, phosphate and other mineral resources, so it is a new area worthy of attention. The Qinling trough and western Hubei trough are favorable areas for exploration of natural gas(including shale gas) and mineral resources such as phosphate and manganese ore.

Reconstruction and petroleum geological significance of lithofacies paleogeography and paleokarst geomorphology of the Middle Permian Maokou Formation in northwestern Sichuan Basin,SW China

Based on analysis of outcrop,drilling,logging and seismic data,and geotectonic background,the lithofacies paleogeography and paleokarst geomorphology of the Middle Permian Maokou Formation in the northwestern Sichuan Basin were reconstructed,and the petroleum geological significance of the lithofacies paleogeography and paleokarst geomorphology were discussed.The Maokou Formation is divided into 3 long-term cycles,namely LSCl,LSC2 and LSC3,which correspond to the Member 1,Member 2 and Member 3 of the Maokou Formation,respectively.Controlled by the extensional structure caused by opening of the Mianlue Ocean in the north margin of the upper Yangtze blocks and basement faults produced by mantle plume uplifting,the area had tectonic differentiation in NWW and NE,and sedimentary basement took on episodic settlement from north to south,as a result,the sedimentary systems of Member 1 to Member 3 gradually evolved from carbonate platform to platform-slope-continental shelf.According to the residual thickness,paleokarst geomorphologic units such as karst highland,karst slope and karst depression at different stages were reconstructed.The karst geomorphological units were developed successively on the basis of sedimentary geomorphology.Sedimentary facies and paleokarst geomorphology are of great significance for oil and gas accumulation.The Maokou Formation in northwestern Sichuan has two kinds of most favorable reservoir zone combinations:high energy grain shoal and karst monadnock,platform margin slope and karst slope.Based on this understanding,the planar distribution of the two kinds of reservoir zones were predicted by overlapping the favorable reservoir facies belt with paleokarst geomorphology.The study results provide a new idea and reference for the exploration deployment of the Middle Permian Maokou Formation in the Sichuan Basin.

The Lithofacies Paleogeography and Paleoenvironmental evolution of the Cenozoic in the Weihe Basin, China

The Weihe Basin,which is known as a Cenozoic rift Basin,is special for its location where not only enrich oil,gas and water,but also is a"sweet"for environment evolution research.It sits in the transition area between the ordos basin with full of oil and gas resources in the north and the Qinling Orogenic Belt with rich mineral