Search Results (6)

Fine-grained sedimentary rocks are ideal carriers for astronomical cycle analysis as they can record and preserve significant astronomical cycle signals. Spectral analysis using the Multi-taper Method (MTM) and Evolutionary Harmonic Analysis (EHA) using the Fast Fourier Transform (FFT) were conducted on natural gamma data from key wells in the Es₃l sub-member in the Bonan Sag, Bohai Bay Basin, China. Gaussian bandpass filtering was applied using a short eccentricity cycle of 100 ka, and a “floating” astronomical time scale for the Es₃l sub-member (Lower 3rd sub-member of Shahejie Formation in Eocene) was established using magnetic stratigraphic ages as boundaries. Stratigraphic divisions were made for single wells in the Es₃l of the Bonan Sag, and a stratigraphic framework was established based on correlations between key wells. The research results indicate the following: Firstly, the Es₃l of the Bonan Sag records significant astronomical cycle signals, with an optimal sedimentation rate of 8.39 cm/ka identified. Secondly, the cyclical thicknesses corresponding to long eccentricity, short eccentricity, obliquity, and precession cycles are 38.9 m, 9.7 m, 4.6–3.4 m, and 1.96–1.66 m, respectively. Thirdly, the Es₃l sub-member stably records 6 long eccentricity cycles and 26 short eccentricity cycles, and the short eccentricity curve is used as a basis for stratigraphic division for high-precision stratigraphic correlations. Fourthly, the quality of sandstone-interbedded mudrock is jointly controlled by the short eccentricity and precession. Eccentricity maximum values result in thicker sandstone interlayers, while minimum precession values promote the thickness of sandstone interlayers. Through astronomical cycle analysis, the depositional evolution mechanism of sandstone-interbedded mudrock is revealed. Combined with the results of high-precision stratigraphic division, this can provide a basis for fine evaluation and “sweet spot” prediction of lacustrine shale oil reservoirs. Full article

Properly determining reservoir wettability is crucial for enhancing oil recovery and optimizing production strategies; this is particularly the case for tight oil reservoirs. The lower-fourth member of the Shahejie Formation (Es4x) in the Bonan Sag of the Bohai Bay Basin is a typical tight sandstone play, which is characterized by a low permeability and poor fluid mobility and quite variable daily production. Despite efforts in reservoir stimulation, the incremental production remains negligible. A detailed investigation of the reservoir wettability was carried out using four representative tight sandstone samples from Es4x to better understand the production behavior of the tight oil reservoir. We employed a suite of analytical methods, including Environmental Scanning Electron Microscopy, contact angle measurement, spontaneous imbibition, and Nuclear Magnetic Resonance, to comprehensively evaluate the wettability characteristics of the reservoir at different scales. Two samples, C1 and C2, exhibit oil-wet characteristics at both pore and macro scales, with Sample C1 showing weak oil-wet behavior and Sample C2 demonstrating strong oil-wet behavior. In contrast, the other samples, C3 and C4, display strong water-wet characteristics across different scales. The pore size threshold between water-wet and oil-wet conditions for samples C1 and C2 is 0.1 μm, while that for samples C3 and C4 is 1 μm. Grain-coating chlorite and grain-coating illite are the primary clay minerals contributing to the oil-wet pore walls of the reservoir, whereas dispersed sheet-like chlorite and rosette chlorite predominantly exhibit water-wet characteristics. The tight oil reservoir in Es4x exhibits pronounced wettability heterogeneities, with distinct regions displaying either oil-wet or water-wet characteristics, significantly impacting the mobility and producibility of the tight oil in this reservoir interval. Full article

In the Bonan area, the lower fourth member of the Shahejie Formation (Es4x) is buried beneath a sedimentary pile ranging from 2500 to 5000 m. Understanding the impact of diagenetic alterations on these deeply buried reservoirs is crucial for effective hydrocarbon exploration and production. This study employs a terminal fan sedimentation model, encompassing depositional environments such as feeder channels, distributary channels, floodplains, and basinal zones, to provide insights into the spatial distribution of reservoir properties and their influence on the localization of optimal reservoirs within the sag. The analysis integrates diagenetic facies with well log responses, subsurface porosity trends, and permeability variations across the formation. The petrographic analysis indicates that the sandstone is composed primarily of litharenite, feldspathic litharenite, lithic arkose, and minor amounts of arkose. The dominant clay cement is illite, accompanied by mixed-layer smectite/illite, chlorite, and kaolinite. Thin section observations reveal secondary porosity formed through the dissolution of quartz grains, volcanic rock fragments, and feldspar, along with their associated cements. These sandstones exhibit relatively good sorting, with average porosity and air permeability values of 14.01% and 12.73 mD, respectively. Diagenetic alterations are categorized into three processes: porosity destruction, preservation, and generation. Key diagenetic mechanisms include compaction, cementation, replacement, and dissolution, with compaction exerting the most significant control on reservoir porosity reduction. Statistical analysis indicates that the average porosity loss due to compaction is approximately 13.3%, accounting for about 38% of the original porosity. The detrital rock cement predominantly comprises quartz (42%), feldspar (32%), clay minerals (14%), and carbonate (12%). Under the prevailing depositional conditions, porosity is enhanced by dissolution and fracturing, while late-stage diagenetic cementation by clay and carbonate minerals—excluding chlorite—adversely affects reservoir quality. Consequently, the distributary zone is identified as the primary target for exploration. Full article

The high exploration and development production capacity of the Jiyang Depression, Bohai Bay Basin, China in the early stage confirms the huge exploration and development potential of shale oil in the study area. Due to the complexity of the depositional mechanism in the study area, the distribution law of fine-grained sedimentary rocks is not well understood, which restricts further exploration breakthroughs. This paper comprehensively observes rock cores and thin sections, combines mineral components, Rock-Eval pyrolysis, rock-cutting logging and logging data to classify lithofacies, and clarifies the distribution law of various lithofacies. The research results show that, according to lithological characteristics, various lithofacies origins are classified into three categories: terrigenous, mixed, and endogenous sources, and six lithofacies types are distinguished: terrigenous low-organic-matter massive siltstone (LF1), terrigenous low-organic-matter massive mudstone (LF2), mixed-source medium-organic-matter massive mudstone (LF3), mixed-source medium-to-high-organic matter laminated-massive mudstone (LF4), mixed-source medium-to-high-organic-matter laminated mudstone (LF5), and endogenous-sourced medium-to-high-organic matter laminated limestone (LF6). The distribution of lithofacies in plane is symmetrical in the east–west direction and is characterized by a banded distribution; the distribution in profile shows a stable depositional process and a continuous depositional sequence. The various lithofacies depositional models have been summarized; the terrigenous input from the northern steep-slope zone has influenced the hydrodynamic conditions of the lake basin, significantly affecting the lithofacies depositional variations from the steep-slope zone to the deep-sag area. The geological evaluation of each lithofacies has been conducted; LF1 + LF4 + LF5 are classified as Class I—target reservoirs for shale oil development, while LF3 + LF6 are considered Class II—favorable reservoirs. The result of the study provide a reference for the classification of fine-grained sedimentary-rock facies and distribution characteristics, and the evaluation of shale-oil-reservoir sweet spots in graben lake basins. Full article

As the world’s energy demand continues to expand, shale oil has a substantial influence on the global energy reserves. The third submember of the Mbr 3 of the Shahejie Fm, characterized by complicated mudrock lithofacies, is one of the significant shale oil enrichment intervals of the Bohai Bay Basin. The classification and identification of lithofacies are key to shale oil exploration and development. However, the efficiency and reliability of lithofacies identification results can be compromised by qualitative classification resulting from an incomplete workflow. To address this issue, a comprehensive technical workflow for mudrock lithofacies classification and logging prediction was designed based on machine learning. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were conducted to realize the automatic classification of lithofacies, which can classify according to the internal relationship of the data without the disturbance of human factors and provide an accurate lithofacies result in a much shorter time. The PCA and HCA results showed that the third submember can be split into five lithofacies: massive argillaceous limestone lithofacies (MAL), laminated calcareous claystone lithofacies (LCC), intermittent lamellar argillaceous limestone lithofacies (ILAL), continuous lamellar argillaceous limestone lithofacies (CLAL), and laminated mixed shale lithofacies (LMS). Then, random forest (RF) was performed to establish the identification model for each of the lithofacies and the obtained model is optimized by grid search (GS) and K-fold cross validation (KCV), which could then be used to predict the lithofacies of the non-coring section, and the three validation methods showed that the accuracy of the GS–KCV–RF model were all above 93%. It is possible to further enhance the performance of the models by resampling, incorporating domain knowledge, and utilizing the mechanism of attention. Our method solves the problems of the subjective and time-consuming manual interpretation of lithofacies classification and the insufficient generalization ability of machine-learning methods in the previous works on lithofacies prediction research, and the accuracy of the model for mudrocks lithofacies prediction is also greatly improved. The lithofacies machine-learning workflow introduced in this study has the potential to be applied in the Bohai Bay Basin and comparable reservoirs to enhance exploration efficiency and reduce economic costs. Full article

The middle sub-member (Es3z) within the third member (Es3) of the Eocene Shahejie formation is the main source of the generation and accumulation of hydrocarbons in the lacustrine deltas of Bonan depression. Exploration and research work in different blocks is carried out separately. Types of sedimentary facies, and their vertical and lateral evolution in Es3z are not studied in detail. To fill this knowledge gap, we did a detailed analysis of facies and lithological characteristics through integrative studies of cores, well logs and seismic data. Identification of sedimentary structures and lithology of the reservoir zone from cores are calibrated with high-quality well logs and seismic data. Depositional facies in Es3z reservoirs are identified through analysis of sedimentary structures, grain size, log’s trends and seismic sections. Es3z was deposited in the fan delta front setting where five facies associations are found, among them distributary channels consisting of MCS, CSg, PCSs, MS, RCL, WCS, PBSs, RCS and GBS lithofacies, natural levee containing DFs, and furthermore, sheet sand are associated to CBS and SSM lithofacies. GM, GGM and DGM lithofacies are related to inter-distributary deposits, whereas mouth bars consist of PLS, CS and CFS. Depositional history, flow direction of the sediments, and facies distribution are investigated through detailed facies mapping and cross-section profiling to show that the sediments were sourced from southeast to northwest. We found thicker succession of sedimentary profiles towards north and north-west directions. Belt distributary channel deposits, covering a wide range of areas, act as potential reservoirs along with mouth bar deposits, while mudstones in interdistributary channels act as a good source and seal rocks. The methodology adopted has great potential to explore the reservoirs of fan delta front in lacustrine deltas. Full article