Lithofacies Types Research Articles

Provenance of the Upper Carboniferous Yanghugou Formation in the Western Margin of the Ordos Basin, China: Constraints on Paleogeography and Basin Development

The Carboniferous Yanghugou Formation in the western margin of the Ordos Basin exhibits significant potential for oil and gas exploration. However, due to the influence of complex tectonic activities, there are substantial variations in stratigraphic thickness and depositional environments across the formation. The lack of a systematic source–sink comparative study has resulted in an unclear understanding of sediment sources and paleogeographic patterns, impacting the exploration for hydrocarbon accumulations. We conducted a comprehensive study of the source–sink system characteristics and paleogeography in the research area through field outcrop observations and drilling core sampling. By utilizing detrital zircon U–Pb geochronology and geochemistry, paleocurrent directions, lithofacies types, and sedimentary features, we delve into the understanding of the source–sink systems. Four major source–sink regions in the research area were identified: the Alxa, Yinshan, Alxa–Yinshan mixed and Qilian source–sink regions. The Alxa source–sink region formed a transitional delta-barrier-island sedimentary system. The northern part of the Yinshan source–sink region developed a transitional tidal-controlled delta-tidal-flat sedimentary system, while the southern deep-water area developed a shallow marine to semi-deep marine shelf sedimentary systems. The sediments of Alxa–Yinshan mixed source–sink region were deposited in a transitional tidal-controlled delta-tidal-flat barrier-island system. The Qilian source–sink region is characterized by small tidal-controlled delta-barrier-island system. From the analysis of the source–sink systems, it is inferred that the Alxa Block and the North China Craton had already merged before deposition of the late Carboniferous Yanghugou Formation. The delta sand bodies in the Alxa–Yinshan mixed source–sink region have the highest compositional and structural maturity, the best reservoir performance, and the great exploration potential.

Lithofacies characteristics and genetic mechanism of hybrid sedimentary rocks in Da'anzhai member, Sichuan Basin

The Jurassic Da'anzhai Member in the Sichuan Basin is a stratigraphic unit characterized by widespread mudstone and hybrid sedimentation. It comprises various lithofacies types and sedimentary structures, including massive structure, laminated structure, mud rip-up clasts and erosion surfaces. By means of detailed analysis of core, logging, thin sections, scanning electron microscope, XRD and XRF data, six lithofacies types are identified in the Da'anzhai Member, and the genetic mechanisms of these lithofacies such as sandy debris flow, turbidity current, bioclastic flow and still water sedimentation are analyzed based on the characteristics of lithofacies. A complete third-order cycle was identified in the LA 1 and RA 1 well based on the variation in the value of gamma ray, bioclastic content as well as lithofacies characteristics. The paleo-sedimentary environment of Da'anzhai Member of Sichuan Basin is reconstructed on the basis of geochemical proxies such as Sr/Cu, Ca/(Ca + Fe), V/(V + Ni), V/Cr, Ti, Al, Al/(Al + Fe) and Fe/Mn. Different sedimentary environments in the Da'anzhai Member controlled the characteristics of lithofacies distribution and the lake level (water depth) primarily controlled the scale and frequency of the development of hybrid sedimentation and mudstone. During the early and late sedimentary periods of the Da'anzhai Member, the climate was arid, water salinity was high, reducing conditions were weak, and the water body was deep. Sediments such as sandy and bioclastic materials in shallow areas were transported to deeper areas through gravity flows under the influence of sudden events like earthquakes, floods or storms and interbedded with still water mudstones. In the middle period of the Da'anzhai Member, the climate was humid, water salinity was low, reducing conditions were strong, and the water body remained deep. A large amount of deep-water mudstone developed in this period, with gravity flow deposits appearing as thin layers. Finally, the comprehensive sedimentary model of the study area is completed based on this characteristics.

Pore development characteristics and controlling factors of Lower Cambrian Qiongzhusi shale gas reservoir in Sichuan Basin, China

Recently, the shale gas exploration of Lower Cambrian Qiongzhusi Formation in Sichuan Basin has made a great breakthrough. However, the pore characteristics and controlling factors of the shale-gas reservoir in the Qiongzhusi Formation are not clear, which hinders further exploration and development of shale gas. This paper focuses on the Qiongzhusi Formation in the Lower Cambrian of the Sichuan Basin. On the basis of mineral composition and the lithofacies types of shale-gas reservoirs in Qiongzhusi Formation were classified by microscopic observation. Additionally, focused ion beam-scanning electron microscope (FIB-SEM), advanced mineral identification and characterization system (AMICS) analysis, large-field stitching scanning electron microscope technology (MAPS) and nitrogen adsorption experiment were employed to comprehensively determine the differential characteristics and controlling factors of pore development. The results indicate that the pore types in Qiongzhusi Formation are mainly composed of interparticle pores and intercrystalline pores. The pore structure of Qiongzhusi Formation is complex. Significant differences in pore structure parameters are observed among different lithofacies. Quartz and feldspar contribute to the preservation of primary pores due to their strong compressive resistance. Clay minerals and carbonate minerals impede pore development by occluding pores. The influence of organic matter on the pore development is relatively small. According to the mineral composition and pore parameters, laminated shale is a relatively favorable reservoir facies among different lithofacies types.

Characteristics and genesis of tuffaceous shale oil lithofacies:A case study of Lucaogou Formation in Santanghu Basin

Lucaogou Formation in the Santanghu Basin is a special lacustrine fine-grained sedimentary deposits rich in volcanic debris and carbonate, with abundant shale oil resources. However, understanding of shale oil characteristics and genesis remains unclear. Lithofacies, sedimentary environment, and formation mechanisms of tuffaceous shale oil are investigated based on core and thin section observations, X-ray diffraction, field emission SEM and geochemical analysis. Results show that three mixed lithofacies types are developed in Lucaogou Formation: blocky tuff, laminated tuffaceous dolomite, and laminated dolomitic tuff. These lithofacies types are characterized by high content of felsic and dolostone, widespread organic matter, and low clay content. Formation of tuffaceous shale oil sweet spots is primarily influenced by four factors: inputting of volcanic ash as a high-quality source rocks and reservoirs provides good material basis; devitrification of volcanic glass, calcitization, and dissolution are crucial for formation of reservoirs; expulsion of source rocks with high-abundance organic matter expulsion facilitates migration and accumulation of hydrocarbon in adjacent reservoirs; fracture development improves reservoir permeability to form highly productive sweet spots. By analyzing characteristics and genesis of tuffaceous shale oil, the main controlling factors of reservoir physical property and oil saturation are clarified, which is of great significance for selection of shale oil exploration zones.

Lithofacies identification from well-logging curves via integrating prior knowledge into deep learning

Lithofacies is a key parameter in reservoir characterization. With advances in machine learning, many researchers have attempted to predict lithofacies from well-log curves by using a machine-learning algorithm. However, existing models are built purely on data, which do not provide interpretability. In addition, lithofacies distribution is highly imbalanced. We incorporate domain knowledge into a gated recurrent unit network to force the model to learn from the data and knowledge. The domain knowledge that we use is expressed as first-order logic rules and is incorporated into the machine-learning pipeline through additional loss terms. Specifically, these rules are: (1) if the density is smaller than or equal to [Formula: see text], then the lithofacies is coal; (2) if the density is larger than or equal to [Formula: see text] or the neutron porosity is smaller than or equal to [Formula: see text], then the lithofacies is anhydrite; and (3) if the gamma-ray value is larger than or equal to [Formula: see text], then the lithofacies is shale. Here, [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] are the parameters that are learned by the model. By applying this domain knowledge, we aim to elucidate why the model predicts lithofacies as coal, anhydrite, or shale and reduce the effect of imbalanced data on the model’s performance. We evaluate the method on a data set from the North Sea, and the machine-learning pipeline with domain knowledge embedded is slightly superior compared with the baseline model that does not consider domain knowledge. One drawback of the method is that the domain knowledge that we provide only works for coal, anhydrite, and shale, which is incomplete. In future work, we will attempt to develop more rules that work for other types of lithofacies.

Sedimentary texture differences between lithofacies types and their control on the physical property in fan-delta conglomerate reservoirs: A case study from the Triassic Baikouquan Formation in Mahu Sag, Junggar Basin, Northwestern China

Conglomerate reservoir developed in fan-delta environment is characterized by the diverse lithofacies types and strong heterogeneity. Lithofacies type is the main primary factor that controls the reservoir physical properties. However, quantitative sedimentary texture parameters of lithofacies types are scarcely studied, and their influence on the reservoir physical properties are still poorly understood. In this paper, lithofacies type, sedimentary texture and pore type, porosity and permeability of the Baikouquan Formation in Mahu Sag were studied to reveal the control of sedimentary texture parameters on the reservoir physical properties.The results showed that (1) lithofacies types in Baikouquan Formation can be classified into Gcm1, Gcm2, Gcm3, Gcm4, Gc, Sm1, Sm2, MSm, SSr, SSp and Mh; (2) different sorting coefficient and matrix content are present in Gcm, Gc, Sm1, Sm2 and MSm. These two texture parameters are highest in Sm2 and MSm, below Gcm and Gc, and the lowest in Sm1; (3) intra-gravel microfracture, gravel-edge microfracture and intra-matrix microfracture develop in conglomerates, which can improve their permeability; (4) porosity in Gcm, Gc, Sm1, Sm2 and MSm and permeability in Sm1, Sm2 and MSm have negative correlations with their sorting coefficient and matrix content. However, permeability in Gcm and Gc have poor correlations with these two texture parameters due to microfractures; (5) Gc and Sm1 have relatively high porosity and permeability due to their good sorting, low matrix content and consequently strong dissolution. By contrast, Gcm, Sm2 and MSm have relatively low porosity and permeability due to their bad sorting, high matrix content and consequently weak dissolution. These results indicate that Gc and Sm1 deposited in subaqueous distributary channels and lobes should be the first target in hydrocarbon exploration of fan-delta conglomerate reservoir.

Reservoir Petrofacies Predicted Using Logs Data: A Study of Shale Oil from Seven Members of the Upper Triassic Yanchang Formation, Ordos Basin, China

The identification and prediction of petrofacies plays a crucial role in the study of shale oil and gas “sweet spots”. However, the petrofacies identified through core and core test data are not available for all wells. Therefore, it is essential to establish a petrofacies identification model using conventional well logging data. In this study, we determined the petrofacies of shale oil reservoirs in the Upper Triassic Yanchang Formation, Ordos Basin, China, based on scanning electron microscopy, core porosity and total organic carbon (TOC), and brittleness index calculations from X-ray diffraction (XRD) experiments conducted on seven members of the formation. Furthermore, we compared the interpreted logs with the raw well logs data clustered into electrofacies in order to assess their compliance with the petrofacies, using the Multi-Resolution Graph-Based Clustering (MRGC) method. Through an analysis of pore structure type, core porosity, TOC, and brittleness index, we identified four types of lithofacies with varying reservoir quality: PF A > PF B > PF C > PF D. The compliance of the clustered electrofacies with the petrofacies obtained from the interpreted logs was found to be 85.42%. However, the compliance between the clustered electrofacies and the petrofacies obtained from the raw well logs was only 47.92%. Hence, the interpreted logs exhibit a stronger correlation with petrofacies characterization, and their utilization as input data is more beneficial in accurately predicting petrofacies through machine learning algorithms.

Rock Typing and Characterization of the Late Cretaceous Abu Roash "G" Reservoirs at East Alam El-Shawish Field, Western Desert, Egypt

Rock typing and petrophysical characterization play a vital role in constructing reservoir models for petroleum exploration and development. This study focuses on evaluating the petrophysical characteristics of the Late Cretaceous Abu Roash "G" Reservoirs at the East Alam El Shawish field in Egypt's Western Desert. The study involved five vertical wells and employed various techniques and analyses to investigate the reservoir. Lithology determination utilizing well logs and core analysis helps identify the lithology types and corresponding porosity of the Abu Roash "G" reservoirs. Sandstone and limestone lithologies with varying porosity ranges were identified, along with the influence of shale on neutron porosity values. Facies analysis of the Abu Roash "G" Member identified seven lithofacies types, categorized into shallow marine and deeper marine depositional environments. The petrophysical analysis involves evaluating gamma-ray logs, porosity, permeability, flow zone indicator (FZI), and reservoir quality index (RQI) values for each lithofacies type. This analysis classifies the core samples into seven reservoir rock types (RRT1 to RRT7) based on petrophysical attributes, providing a clear classification of the Abu Roash "G" reservoir interval. RRT1, RRT2, and RRT3 exhibit the highest reservoir quality, while RRT4 and RRT5 indicate moderate reservoir quality. RRT6 and RRT7 exhibit low reservoir quality due to unfavorable petrophysical behavior. The findings of this study provide valuable insights into the Abu Roash "G" reservoir, including its lithofacies, reservoir properties, and depositional environments. This knowledge is crucial for reservoir characterization and optimizing oil production strategies in the region.

Application of Artificial Neural Networks for Identification of Lithofacies by Processing of Core Drilling Data

Identifying lithofacies types from core drilling data presents significant challenges, especially given the limited number of physical drilling characteristics available for analysis. Traditional machine learning methods often face issues with poor training and testing due to these limitations. Addressing this, we propose a new method for processing core drilling data to improve the accuracy of deep artificial neural networks (DANNs) in lithofacies recognition. Our approach transforms torque, weight on bit (WOB), and rotational speed data into three square matrices, creating a novel three-channel lithofacies image. This method allows for the application of DANNs by converting the complex lithofacies recognition task into a more standard image recognition problem. The developed method dramatically increases the input vector dimensions, enhancing the richness of the data input. The validation of results revealed that the DANN model trained for merely 3000 iterations successfully predicted lithofacies types of all eight testing samples in a mere 2.85 ms, showcasing superior accuracy. The innovative drilling data processing method proposed in this study enables DANNs to identify lithofacies with increased speed and accuracy. This offers a new direction for other DANNs utilizing drilling data.

Influence of extractable organic components on shale wettability: Dongyuemiao member of Jurassic Ziliujing formation in the Fuxing area, Eastern Sichuan Basin

The wettability of reservoir rocks is a critical factor for the petroleum exploration and recovery, which plays an important role on relative permeability, capillary pressure, and ultimate recovery. This study aims to characterize the difference in wettability before and after soxhlet extraction, and reveal the influences of mineral composition, pore structure and extractable organic components on wettability of shales with different lithofacies. Several organic shale samples from the Dongyuemiao (DYM) section of the Jurassic Ziliujing (ZLJ) formation were collected to investigate the mineral composition, pore-size distribution, wettability characteristics and determine the main controlling factors on wettability alteration. Pore type and abundant are observed using argon ion polishing scanning electron microscopy. The pore volume (PV) and pore size distribution (PSD) characteristics before and after extraction were obtained using a combination of nitrogen physisorption and high-pressure mercury intrusion porosimetry (MIP). Spontaneous imbibition (SI) and nuclear magnetic resonance (NMR) experiments were used to investigate the wettability characteristics before and after extraction.Results show that clay, quartz and calcite are dominant minerals in the DYM shales, and three typical lithofacies are identified, including mixed shale (M), argillaceous shale (CM) and calcareous shale (C). Clay mineral interP pore is the dominant pore type in the DYM shales, followed by organic matter (OM) pore. Before the extraction, the DYM shale is more oil lipophilic, while its wettability alters slightly after the extraction. The M shales and C shales maintain lipophilic, while as the CM shales alters from oil wet to mixed wet. Samples with higher quartz have better connectivity of the hydrophilic and lipophilic pore networks, and carbonate minerals play an opposite role. During the extraction process, polar solvents could react with clay minerals to cause pore space expansion, which enhances the water wettability after extraction. Due to the low OM content and poor organic clay complex related pores in the study area, clay minerals have not significant correlation with oil wettability, but influence the water wettability. No correlation occurs between total organic carbon (TOC) content and oil/water wettability of shales before and after extraction. In comparison, macropore has a significant impact on water wettability, while micropore and mesopore play significant impact on oil wettability.

Classification of shale lithofacies with minimal data: Application to the early Permian shales in the Ordos Basin, China

Shale lithofacies classification is one of the key components of shale reservoir evaluation. Typically, a significant amount of laboratory X-ray diffraction (XRD) data acquired on many shale samples collected in a large number of boreholes is required to constrain the mineral composition that enables classifying shale lithofacies at the basin scale. This procedure is costly and time consuming. Here, we propose a supervised machine learning method to predict the mineral composition of shale samples, including the clay and silicate content. The main advantage of our approach is that it only uses conventional logging data and a small number of XRD measurements of core samples, combined with XGBoost algorithm, to predict shale lithofacies, which can reduce the cost and improve the efficiency of reservoir evaluation. We apply our method on the early Permian shales in the Ordos Basin, China, because these shale rocks have a high potential of gas production. However, these formations are also highly heterogeneous, making them challenging to explore and exploit. Therefore, it is critical to perform detailed lithofacies classification analysis at the basin scale before gas production. Our result show that the gamma ray, neutron porosity, and density measurements are the critical logging data that control the model predictions. These parameters are known to be sensitive to clay content, thereby supporting the robustness of model predictions. Applying the model to different wells to classify shale lithofacies, results that these shale formations are dominated by three types of lithofacies. We characterize the different shale lithofacies by microscopy images and gas adsorption measurements, and demonstrate that our results are consistent with previous studies, verifying the accuracy and applicability of our machine learning method to classify shale lithofacies.

Low-grade to extremely high-grade ignimbrites and associated deposits of the uppermost Schrikkloof Formation in the Paleoproterozoic Rooiberg Group, Bushveld large igneous province, South Africa

The volcanic rocks of the Schrikkloof Formation of the Paleoproterozoic Rooiberg Group provide crucial information on the eruptive and depositional processes preceding or concurrent with the intrusive activity of the Bushveld large igneous province of South Africa. A study area near the town of Modimolle (formerly Nylstroom), approximately 190 km north of Johannesburg, was chosen due to the relatively good exposure. The results of this study show that all rocks within the study area, ranging in composition from rhyolites to dacites, have been affected in various ways by circulating hydrothermal fluids, the presence of which is demonstrated by existing hydrothermal breccias and fumarolic features. The volcanic rocks are classified into three lithofacies types, which can be interpreted as low-grade, high-grade, and extremely high-grade welded ignimbrites. The ignimbrite-forming eruptions, which may have been characterized by low columns, were possibly fed by fissures (potentially related to one or more as yet unidentified calderas) associated with a reactivation of the Thabazimbi-Murchison Lineament, a prominent suture zone in the north of South Africa that has been reactivated several times since the Archean. A decline in volcanic activity may be seen near the top of the volcanic succession, which is coupled with a continual increase in clastic sedimentation. This demonstrates a gradational relationship between the volcanic-dominated Schrikkloof Formation and the overlying clastic-dominated Swaershoek Formation of the Waterberg Group. Therefore, the findings of this study may have profound implications for the Paleoproterozoic stratigraphy of South Africa, which hitherto considers the Swaershoek Formation to have an unconformable relationship with the Rooiberg Group below. Furthermore, the evidence provided in this article may aid in the identification and interpretation of other high-grade ignimbrites encountered around the world.

Lithofacies variability and facies analysis of a Givetian reef in the southwestern Lahn Syncline (Rhenish Massif, Germany)

A 200 m thick drill core penetrating the Givetian Hahnstätten Reef in the southwestern Lahn Syncline (Rhenish Massif) was investigated. A range of different depositional environments is described based on lithofacies and microfacies analysis. All in all, nine lithofacies types (FTs) are distinguished, which can include subfacies types. The majority of lithofacies of these ultrapure carbonates is represented by lime mudstone and fenestral microbialites, all pointing to shallow subtidal, intertidal to even supratidal low-energy palaeoenvironments. In contrast, more high-energy parts of the reef were dominated by bioclastic rubble deposits (e.g. rudstone). Autochthonous, reef-building carbonates are represented by bafflestone and framestone. Diversity of reef building organisms (stromatoporoids and corals) is low and is dominated by Stachyodes, Actinostroma, Stromatopora, and Thamnopora and alveolitids, respectively. Other bioclasts are brachiopods, gastropods, ostracods, foraminifera, echinoderms, trilobites, and conodonts in descending order. Development of the Hahnstätten Reef is interpreted as having been controlled mainly by synsedimentary tectonics and volcanism with contributions from eustasy. The occurrence of Stringocephalus burtini in the entire section and conodont findings, which provide more precise biostratigraphic data confirm an early to middle Givetian age (Polygnathus rhenanus/varcus Zone to Polygnathus ansatus Zone) of the succession. The average quality of the ultrapure carbonates lies at 97.68% CaO (excl. loss of ignition), with 70% of the core ranging between 98% and 99% CaO. This extremely high purity makes it difficult to identify correlations between lithofacies and geochemical data.

Identifying lithofacies types by boosting algorithm and resampling technique: a case study of deep-water submarine fans in an oil field in West Africa

The continuous discovery of giant oil and gas fields in deep-water low stand fans has made deep-water submarine fan reservoirs with huge oil and gas potential important targets for oil and gas exploration and development. Nowadays, machine learning algorithm has been proven to be an effective method to classify various rock types from geophysical logging data, but rarely has there been focus on predicting deep-water submarine fans in previous studies. In this paper, we utilized five classical Boosting machine learning algorithms, namely GBDT, XGBoost, LightGBM, CatBoost, and LogitBoost, to identify 14 deep-water submarine fan lithofacies types from 7 wells in a West African oilfield. To address the sample non-balance problem, we employed SMOTE and MAHAKIL oversampling techniques and optimized the hyperparameters of the model using Genetic Algorithm. The experimental results show that the model performance is improved by using oversampling technologies and hyperparameter optimization. The proposed MAHAKIL-GA-GBDT algorithm is the most effective in identifying the lithofacies of deep-water submarine fans, with an accuracy of 0.986. This study provides a new approach for identifying deep-water submarine fan lithofacies and highlights the potential of machine learning algorithms in this field.

Volcanosedimentary fill of the early Cretaceous Yingcheng formation and response to the end of continental rifting in the Songliao Basin: Constraints from well SK-2, northern Xujiaweizi fault depression

Well SK-2 of the International Continental Scientific Drilling Project (ICDP) obtained continuous core samples with a length of 365.32 m in the Early Cretaceous Yingcheng Formation, showing a stratigraphy of interbedded rhyolites and coarse clastic rocks in the Xujiaweizi fault depression. The Yingcheng Formation in well SK-2 is divided into three sequences. Sequences 1 (S1) and 3 (S3) consist of coarse clastic rocks, and four types of conglomerate lithofacies are identified. The conglomerate lithofacies of S1 is characterized by gravity flows. In comparison, the conglomerate lithofacies of S3 is characterized by a progradational braided channel, reflecting a proximal provenance and a shallowing upward setting. Sequence 2 (S2) rocks are rhyolites, and geochemical analysis shows these to have mainly originated from the middle-upper crust. On the basis of volcanic rocks in wells Shengshen 2–1 and Shengshen 203 and seismic profiles crossing these wells, we identify two types of volcanic edifices: stratovolcanoes in the east and shield volcanoes in the west. The Early Cretaceous strike-slip faults, including the Xuzhong and Xudong faults, play an important role in controlling this area. In comparison with extensive, dark, and fine-grained clastic rocks of the Shahezi Formation, the felsic and coarse clastic rocks of the Yingcheng Formation in well SK-2 mark a sedimentary response to strike-slip tectonics and indicate the ending fault movement of the Xujiaweizi fault depression, and perhaps even the end of the Early Cretaceous Songliao Basin rifting stage.

Geochemical evolution of the Doushantuo economic phosphorite in Central Guizhou, South China: Quantified multi-stage metallogenic process

Economic phosphorite from Ediacaran Doushantuo Formation is the first true phosphorite giant and represents the onset of the Precambrian-Cambrian global phosphogenic event. The Doushantuo phosphorite may have deposited during the early-middle Ediacaran (ca. 632–574 Ma) according to the latest radiochronological data. Petrographically, in central Guizhou, it can be subdivided into two types of lithofacies: pristine phosphorite (micritic phosphorite, phosphatic shale, banded phosphorites) and reworked phosphorite (intraclastic phosphorite, vuggy intraclastic phosphorite, unconsolidated phosphorite). Geochemical data show that chemical/biochemical enrichment is the most effective process to condense the phosphatic sediments and obviously improve the grade of P2O5 (can reach 38.8 wt%). Hydrodynamic reworking may not play an important role in the further enrichment of P2O5 content but effectively got rid of SiO2 and Al2O3 components in phosphorite by the removal of lighter terrigenous particles and clays. Mass change calculation shows that Ca and Mg are heavily depleted in the chemical leaching process, implying it is a key process to upgrading the quality of phosphorite by separating the carbonate constituents from phosphorite. Therefore, a multi-stage metallogenic model of chemical/biochemical enrichment, hydrodynamic reworking, and chemical leaching is proposed, quantified the composition changes and elucidated the constrained factors in the formation of high-graded phosphorite. Such a metallogenic process effectively produced high-quality phosphorite deposits and bring great benefits to metallurgy.

Sedimentary Facies Types and Their Control of Reservoirs in the Lower Jurassic Lacustrine Facies Shale of the Lianggaoshan Formation, Northeastern Sichuan Basin, China

In recent years, new breakthroughs have been made in the field of shale oil and gas exploration in the Lower Jurassic Lianggaoshan Formation in Sichuan Basin. At present, there is a lack of systematic studies on reservoir properties and sedimentary facies of the Lianggaoshan Formation shale. Therefore, in this study, taking the Lianggaoshan Formation in Sichuan Basin as an example, the sedimentary facies types of shale reservoirs and their control over shale oil and gas are systematically studied, based on a large number of outcrops, experimental testing, logging, and seismic interpretation methods. The results show that five sedimentary microfacies are developed in the Lianggaoshan Formation in the study area, namely, semi-deep lake mud, shallow lake mud, wave-influenced shallow lake mud, delta-influenced shallow lake mud, and underwater interbranch bay microfacies. The stratum thickness of the Lianggaoshan Formation is in the range of 26–315 m, and mainly distributed in the eastern region, but rapidly thinned in the northwestern region. The sedimentary sequence framework of the Lianggaoshan Formation has been constructed. Moreover, the lithology of the Lianggaoshan Formation shale has been divided into three types, including shale, massive mudstone and silty mudstone. The brittleness index and total organic carbon (TOC) value of three types of shale show a negative correlation. Silty mudstone has the highest brittleness, while that of black shale is the lowest. For porosity and permeability, massive mudstone is better than silty mudstone, and silty mudstone is better than black shale. There are many kinds of matrix pores in the Lianggaoshan Formation shale, and the development degree of inorganic pores is higher than that of organic pores. Finally, based on the analysis of oil-bearing, pore types, physical properties and productivity, it is considered that black shale facies is the most favorable lithofacies type. The deep–semi-deep lacustrine facies belt obviously controls the shale oil enrichment of the Lianggaoshan Formation.

Clay mineral transformation mechanism modelling of shale reservoir in Da’anzhai Member, Sichuan Basin, Southern China

Shale reservoirs often undergo intense clay mineral transformation, which plays a crucial role in the formation and evolution of pores. The reservoir lithofacies types of Da’anzhai Member in the Sichuan Basin are complex, the heterogeneity is strong, and the transformation mechanism of clay minerals is unclear, limiting the understanding of reservoir diagenesis and reservoir formation mechanism. In this study, we selected the typical shale reservoir in the Da’anzhai Member of the eastern Sichuan Basin and innovatively introduced the multiphase fluid-chemical-thermal multi-field coupled numerical simulation technique to focus on the dissolution, precipitation and transformation laws of diagenetic minerals in the shale reservoir. We calculated the transformation of diagenetic minerals and their physical response under different temperatures, pressure and fluid conditions and identified the main controlling factors of mineral transformation in shale reservoirs in the study area. The results show that the transformation of smectite to illite in the Da’anzhai Member is a complex physicochemical process influenced by various factors such as temperature, pressure, fluid, and lithology. The increase in temperature can promote illitization until the critical temperature of 110°C–115°C, below which the conversion rate of smectite to illite increases as the temperature increases. However, when it is higher than the critical temperature, the degree of illitization decreases. In specific K-rich fluids, organic acids significantly affect the conversion of clay minerals in the Da’anzhai Member of the formation. The acidic fluid promotes the dissolution of minerals such as K-feldspar and releases K+, thus provides the material basis for illitization. The research results provide theoretical support for the diagenetic and formation mechanism of the shale reservoir in the Da’anzhai Member of the Sichuan Basin and even for the efficient exploration and development of shale gas.

Characteristics and Paleoenvironment of High-Quality Shale in the Triassic Yanchang Formation, Southern Margin of the Ordos Basin

A set of high-quality lacustrine shales at the bottom of the Chang 7 member of the Yanchang Formation in the Ordos Basin is one of the main source rocks of tight oil and gas and shale oil in the Yanchang Formation. Based on outcrop, core, drilling and seismic data, by the quantitative characterization of outcrops, fine characterization of logging facies and seismic facies, and geochemical tests, the lithofacies types, geophysical response characteristics and organic geochemical characteristics of this high-quality shale are clarified, and the formation paleoenvironment, including redox conditions, paleoclimate, paleosalinity and paleowater depth, is analyzed. The high-quality shale at the bottom of the Chang 7 member is divided into three lithofacies types: black shale, dark massive mudstone and silty mudstone. The organic matter in black shale is mainly interbedded or stratified, the organic matter in dark massive mudstone is dispersed and the organic matter content in silty mudstone is lower. The shale shows high gamma (more than 260 API), a high acoustic time difference (more than 280 μs/m), a high resistivity (more than 330 Ω m) well-logging phase and strong-amplitude parallel–subparallel seismic phase characteristics. Based on the logging and seismic facies characteristics, the plane distribution range of this set of shales is defined. The sedimentary thickness gradually increases from the edge (5–10 m) to the center of the basin, among which the Jiyuan–Huachi–Yijun black shale has the largest thickness (more than 30 m). This set of high-quality shales was mainly formed under a warm and humid paleoclimate, in water depths of 60–120 m, and in an anaerobic reducing and continental freshwater paleoenvironment. The fine identification, distribution range and formation conditions of black shale lithofacies are of practical significance for predicting the distribution of favorable lithofacies of shale oil and gas and the deployment of horizontal wells.

Petrological Characteristics and Hydrocarbon Generation of Carbonate Source Rocks of the Permian Taiyuan Formation in Central and Eastern Ordos Basin, China

In order to evaluate the hydrocarbon generation potential and effectiveness of the carbonate source rock from the Lower Permian Taiyuan Formation of the Upper Paleozoic gas reservoirs in the central and eastern Ordos Basin, 87 core samples from the formation were analyzed through the comprehensive application of core observation, thin section analysis, lithofacies division, and organic geochemistry experiments. The results show that the carbonate source rocks of the Taiyuan Formation comprise four lithofacies types with type I–II kerogen: laminar argillaceous micritic limestone, massive micrite, massive bioclastic micritic limestone, and massive algae-clotted limestone. Among them, laminar argillaceous micritic limestone and massive micrite are favorable lithofacies for high-quality source rocks, with a TOC distribution range of 0.99% to 6.07% (average 2.56%) and 0.24% to 8.27% (average 1.77%), respectively. Hydrous gold tube pyrolysis showed that the samples of laminar argillaceous micritic limestone and massive micrite attained a peak yield of nearly 115.0 mL/g TOC (heating rate 2 °C/h) and 101.4 mL/g TOC (heating rate 2 °C/h), respectively, for C1–5 compounds. Due to the higher maturity of the samples, the hydrocarbon gases were dominated by residual kerogen pyrolysis gases and lacked liquid hydrocarbon cracking gas. Furthermore, the carbonate source rocks had weak methane absorption ability, with a maximum adsorption capacity of only about 0.15 cm3/g. In addition, the hydrocarbon gas generation of carbonate source rocks of the Taiyuan Formation was far greater than 0.2 mL/g rock, which is the lower limit standard for effective gas source rock. Therefore, the carbonate source rocks of the Taiyuan Formation should be regarded as important gas source rocks in subsequent explorations of the central and eastern Ordos Basin.