Papers should show the use of any technology that was initially developed for use in conventional oil and gas industries, and show it being applied to either sustainable energy developments or to CCS, subsurface waste disposal or water resources.
Relevant topics include but are not limited to:
1. Exploration & appraisal of the subsurface aspects of geothermal, hydro and wind resources.
2. Appraisal & exploration of developments needed to provide raw materials for solar energy, electric car batteries and other rare earth elements needed for the modern digital society.
3. The use of reservoir modelling, 3D quantification and dynamic simulation for the prediction of subsurface energy storage.
4. The use of reservoir integrity cap-rock studies, reservoir modelling, 3D quantification and dynamic simulation for the development of CCS locations.
5. Quantitative evaluation of porosity, permeability, reactive transport & fracture transport at subsurface radioactive waste disposal sites.
6. The use of petrophysics, geophysics and geology in wind-farm design.
7. The petrophysics and geomechanical aspects of geothermal reservoir characterisation and exploitation including hydraulic fracturing.
Suitable contributions can address, but are not limited to:
A. Field testing and field experimental/explorational approaches aimed at characterizing an energy resource or analogue resources, key characteristics, and behaviours.
B. Laboratory experiments investigating the petrophysics, geophysics, geology as well as fluid-rock-interactions.
C. Risk evaluations and storage capacity estimates.
D. Numerical modelling and dynamic simulation of storage capacity, injectivity, fluid migration, trapping efficiency and pressure responses as well as simulations of geochemical reactions.
E. Hydraulic fracturing studies.
F. Geo-mechanical/well-bore integrity studies.
The global pursuit of clean and sustainable energy has increased interest in hydrogen as a key energy carrier for achieving carbon neutrality. Consequently, global demand for hydrogen is anticipated to grow significantly in both the near and long term, necessitating the development of hydrogen production methods. While several researches have examined hydrogen generation through inorganic processes such as serpentinization, the potential of organic-rich sedimentary formations remains underexplored. This study investigates hydrogen-rich gas generating potential and fracture evolution of organic-rich rocks, with a particular focus on immature shales under controlled thermal treatment, aiming to enhance the yield of clean hydrogen gas. Pyrolysis experiments were conducted to simulate subsurface geological conditions, supported by comprehensive characterization using X-ray diffraction (XRD), X-ray fluorescence (XRF), thermogravimetric analysis (TGA). Gas Chromatography (GC) was used to analyze the gases generated at various heating temperatures and micro-CT imaging was used to examine the samples subjected to varying temperatures. The results show that hydrogen generation increases with temperature, with yields rising from 0.31% at 100°C to 36.02% at 450°C. High-resolution micro-CT imaging shows that thermally induced fractures developed predominantly parallel to bedding planes, enhancing permeability and facilitating gas migration. The progressive decomposition of organic matter, coupled with fracture development, significantly improved hydrogen release efficiency. These findings highlight the potential of organic-rich rocks, as viable and cost-effective targets for natural hydrogen exploration and in situ hydrogen gas generation and offering a pathway toward sustainable subsurface hydrogen exploitation strategies.
How to cite: Kimayim, A., Tawabini, B., Abu-Mahfouz, I., and Yaseri, A.: Exploring the Potential of Organic-Rich Shales for In Situ Hydrogen Production through Thermal Stimulation and Fracturing., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-708, https://doi.org/10.5194/egusphere-egu26-708, 2026.
The geochemical interactions between shale, supercritical carbon dioxied (SC-CO₂ ), and brine play a significant role in determining both the possibility of carbon storage and the long-term stability of shale gas reservoirs. The shale samples were exposed to CO₂-brine-rich environments for a period of 30 days to simulate the in-situ conditions of the shale reservoirs. The pre- and post-analysis were conducted to identify changes in mineralogy, chemical bonding, pore structure, surface texture and morphology. Several analytical techniques, including X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared spectrometry (FTIR), scanning electron microscopy (SEM), and low-pressure gas adsorption (LPGA), were used for characterisation. The results show that significant mineralogical changes occurred to clay minerals and carbonate, accompanied by modification in hydrocarbon functional groups and fluctuation in micropore and mesopore parameters. The consistent variations in pore characteristics are attributed to continuous processes of dissolution- precipitation and development of increased surface roughness due to reaction. The formation of microfractures and the etching effect of the samples were studied using high-resolution SEM images. TGA study confirmed the systematic mass loss caused due to prolonged reactions. These findings indicate that the reservoir integrity and the storage capacity can be affected due to pore structure evolution during geological CO₂ sequestration. Additionally, the changes documented in this study can provide the pathway to improve shale gas recovery, signifying the crucial role of shale formation in global decarbonization efforts
How to cite: Ghosh Dastidar, S., Sarkar, K., Chandra, D., Vishal, V., and Hazra, B.: Experimental Investigation of Geochemical Interactions between Supercritical CO₂ and Shale, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-756, https://doi.org/10.5194/egusphere-egu26-756, 2026.
Oil shale self-heating in-situ conversion technology has emerged as a significant development direction due to its environmental friendliness and cost advantages. However, conventional constant injection-production parameters often lead to inefficient compression energy input and formation oxidation losses, limiting further improvement in energy return ratio (ERR) and oil yield. This study establishes a dynamic optimization model for injection-production parameters in oil shale self-heating in-situ extraction and develops a method for dynamically regulating gas injection rate and oxygen content to enhance process economy and feasibility.Results indicate that under the optimal gas injection parameters (adjustment duration: 120 days, decay rate: 1200, final flow rate: 40 m³/day), the steady-state phase in late production reduces compression energy consumption by 90% and CO₂ production by 48%, significantly decreasing cumulative compression energy input and suppressing hydrocarbon oxidation losses. Consequently, the peak ERR reaches 13.87, representing a 132.33% improvement over constant-rate injection, while oil production increases to 47 m³/m, a 66.9% enhancement. Furthermore, synergistic regulation of oxygen content and injection rate reduces compression energy by an additional 16%, elevating the peak ERR to 14.80—a 6.71% further increase—demonstrating technical feasibility for industrial application. These findings and key parameters provide theoretical and technical support for the large-scale implementation of oil shale self-heating in-situ conversion technology.
How to cite: Zhu, C., Li, Q., Deng, S., Bai, F., and Guo, W.: Dynamic Optimization Control of Injection-Production Parameters for Oil Shale Self-Heating In-Situ Conversion, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1481, https://doi.org/10.5194/egusphere-egu26-1481, 2026.
The mobility and producible volume of shale oil are key factors controlling the effectiveness of shale oil exploration and development and are fundamentally governed by the occurrence state of hydrocarbons within shale pore systems. Consequently, accurate identification and quantitative characterization of oil–water occurrence in shales represent a core scientific challenge in shale oil research. Current investigations rely heavily on fresh or pressure-preserved cores. However, during routine coring, handling, and storage, substantial fluid loss is inevitable, rendering most conventionally cored shale samples unsuitable for in situ fluid-occurrence analysis. Although pressure-preserved coring can effectively maintain original fluid states, its high operational cost severely restricts large-scale application. Therefore, restoring the original pore-fluid occurrence in conventionally cored shales has become a critical technical bottleneck.To overcome this limitation, we develop a novel workflow integrating alternating oil–water spontaneous imbibition with nuclear magnetic resonance (NMR) measurements to recover the original fluid-occurrence state in conventionally cored shales. Pressure-preserved shale cores were first exposed to laboratory conditions to simulate fluid loss during conventional coring. Subsequently, a multistage alternating spontaneous imbibition procedure was implemented using n-dodecane and 15 wt% KCl brine as imbibing fluids to progressively restore the original oil and water contents. Throughout the entire fluid-loss and restoration processes, NMR T₁–T₂ maps were continuously acquired to dynamically monitor variations in oil and water contents and their pore-scale migration behaviour.
The results indicate that shale cores experience rapid oil–water loss during the initial 0–80 h, followed by a markedly reduced loss rate between 80 and 500 h, and reach a quasi-steady state after approximately 500 h, with a cumulative fluid loss of ~45%. During the alternating imbibition procedure, the samples undergo four successive stages, namely primary oil imbibition, water imbibition, secondary oil imbibition, and secondary water imbibition, each approaching a new dynamic equilibrium. After restoration, the oil and water saturations of the conventionally cored shales show strong agreement with those of the corresponding pressure-preserved samples.These findings demonstrate that the proposed method can effectively recover the original pore-fluid occurrence state in conventionally cored shales, enabling reliable characterization of shale oil and water distribution. The workflow is expected to significantly improve the accuracy of shale oil sweet-spot evaluation and provide new technical support for shale reservoir exploration and development.
How to cite: Chen, J. and Wang, M.: Restoring Original Pore-Fluid Occurrence in Conventionally Cored Shales: Insights from Alternating Oil–Water Spontaneous Imbibition and Nuclear Magnetic Resonance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2169, https://doi.org/10.5194/egusphere-egu26-2169, 2026.
Oil and gas reserves are crucial resources for human survival, directly affecting the sustainable development and utilization of future energy. In order to protect the Earth we live on, it is crucial to enhance our understanding and judgment of the trends in oil and gas reserves and to use these resources wisely. To explore new methods for predicting oil and gas reserves, promote sustainable energy development, and provide a theoretical basis for oil and gas exploration and development, this study takes the Neuquén Basin in South America as an example. By combining oil and gas reserve growth data with various geological characteristics and other comprehensive information, a Monte Carlo search + ARIMA algorithm-based method for predicting oil and gas reserves is proposed and applied to the Neuquén Basin for predictive validation. This method analyzes the structural background and divides the basin into structural units to decompose the basin’s reserves into reserves within each structural unit. The reserve growth data from each unit are input into the model, and the parameters required by the model are obtained through Monte Carlo search to produce predictive results. This approach successfully captures the inherent trends of reserve changes and the dynamic features of reserve growth. The method shows significant effectiveness in predicting reserves in the Neuquén Basin, with the predictive model demonstrating high accuracy in fitting.
How to cite: Li, H. and Zhang, L.: oil and gas reserve prediction method based on Monte Carlo Search + ARIMA algorithm: A case study of the Neuquén basin in South America, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2263, https://doi.org/10.5194/egusphere-egu26-2263, 2026.
Abstract
The buried depth of Archean metamorphic buried hill in Bozhong L Oilfield of Bohai Bay Basin is more than 4000 meters, and the matrix porosity and permeability are extremely low. As an effective reservoir space and seepage channel, natural fractures are the core controlling factors for oil and gas enrichment and high yield in buried hills of tight metamorphic rocks. Due to the influence of multi-stage tectonic movement and weathering, the development of buried hill fractures is complex. At the same time, due to the lack of core and imaging logging data, the study of fracture regularity is not systematic. In this study, the data of core, thin section, scanning electron microscope, imaging logging, conventional logging and production performance were comprehensively used to carry out conventional logging fracture identification, and the vertical and plane distribution of fractures and their influence on productivity were clarified. The conventional logging is calibrated by core and imaging logging, and four logging curves sensitive to fractures, such as resistivity difference, density, acoustic time difference and natural gamma, are optimized. The correlation degree between each parameter and fracture is calculated and weighted, and the fracture indication parameter curve is constructed. Compared with the results of fracture identification such as core and imaging logging in the study area and the dynamic data such as leakage, the accuracy of fracture identification based on conventional logging is more than 85 %. In the longitudinal direction, the strong weathered zone is dominated by weathering fractures, with high degree of fracture filling and strong reservoir heterogeneity. The sub-weathered zone develops structures and weathering fractures, which are transformed by dissolution and have high porosity and high permeability. The tight zone only develops regional structural fractures with low porosity and low permeability. The inner fracture zone is dominated by fault-related structural fractures, with low porosity and high permeability. The degree of fracture development is sub-weathered zone > strong weathered zone > inner fracture zone > tight zone. On the plane, fracture development is mainly controlled by faults. With the increase of distance from faults, the degree of fracture development decreases exponentially. The degree of fracture development is significantly positively correlated with productivity. The more developed the fracture is, the higher the productivity is. The research results can provide reference for the characterization of natural fractures in deep metamorphic buried hill reservoirs, and provide geological basis for the efficient development of deep metamorphic buried hill reservoirs in this area.
Key words
Metamorphic buried hills; Conventional logging; Fracture identification; Distribution law; Capacity; Bohai Sea
How to cite: Guo, R., Lv, W., Zeng, L., Du, X., Li, H., and Yin, J.: Study on fracture distribution law of buried hill in deep metamorphic rock : A case study of Bozhong L oilfield in Bohai Bay Basin, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3007, https://doi.org/10.5194/egusphere-egu26-3007, 2026.
Abstract: Natural fractures in tight sandstone reservoirs play an important role in hydrocarbon migration and accumulation. Fracture identification remains challenging due to the scarcity of labeled data and the complex logging responses of fractures. To address these problems, we propose a novel hybrid deep learning framework (CNN-Attention-BiLSTM). First, labeled fracture classification based on Full waveform sonic logs characteristics is employed to screen unlabeled data, replacing sampling algorithms for data balancing. This approach provides more fracture labels that align with authentic geological information. Subsequently, one-dimensional convolution is applied to construct multi-dimensional fracture logging response patterns that characterize fracture development. A Channel Self-Attention is introduced to assign optimal weights to response patterns across different dimensions, achieving an optimized pattern combination. A double-layer BiLSTM is then utilized to mitigate the impact of sedimentary cycles on logging identification, while capturing both short- and long-term dependencies of fracture responses across different network layers. The identification method is applied to the H1 member of the Lower Shihezi Formation in the Hangjinqi area, China. The test set accuracy is higher than 90%, and blind wells verification demonstrates an improvement of over 8% in accuracy compared to conventional methods. The identification results reveal that fractures are the most developed in H1-2, followed by H1-1 and H1-3, while H1-4 is the least developed layer. The fracture distribution pattern is evidently controlled by sedimentary rhythms, with fracture density decreasing in the order: interbedded sandstone and mudstone layers, thick sandstone and thick mudstone, thick mudstone and poorly developed sandstones. This trend is primarily attributed to the thickness of mechanical stratigraphy. Under equivalent tectonic stress conditions, thin sandstone layers are more prone to fracturing due to stress concentration, resulting in higher fracture density. Additionally, the proposed method deepens the correlation between the log response types of fractures and their development degree. It clarifies that fractures occur in varied patterns across different regions. In sandy conglomerates and gravel coarse sandstone intervals with high porosity and permeability, fractures tend to occur as single or multiple parallel fractures and are relatively less developed. fractures are more prevalent in the overlying and underlying intervals. Conversely, in tight sandstone intervals with poor porosity and permeability, the rock is more brittle, leading to the development of dense, interconnected fracture networks. And gas distribution shows correlate strongly with fracture-developed intervals. Therefore, it can be inferred that in intervals with high-quality sandstone reservoirs in the study area, fractures likely serve as vertical conduits connecting upper and lower gas-bearing zones, acting as preferential migration pathways. In contrast, within tight sandstone intervals, fractures primarily enhance matrix reservoir quality, thereby facilitating gas migration and accumulation. The intelligent fracture identification method proposed in this study can provide guidance for the migration, accumulation and efficient development of tight sandstone gas, Further, it can also offer a basis for the later carbon dioxide storage and the construction of underground gas storage of tight sandstone.
Keywords: Fracture identification; Tight reservoirs; Full waveform sonic logs; Conventional logs; Deep learning
How to cite: Liang, B., Zeng, L., and Dong, S.: Intelligent fracture identification and its geological significance in tight sandstone reservoirs., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4140, https://doi.org/10.5194/egusphere-egu26-4140, 2026.
Free hydrocarbon content (S1) is a key parameter for source rock evaluation and sweet spot identification in organic-rich shale reservoirs. Accurate determination of S1 is essential for petroleum exploration; however, traditional measurements rely on expensive core acquisition and Rock-Eval pyrolysis, limiting spatial coverage and operational efficiency. Empirical and log-based models often fail to capture complex non-linear relationships between S1, petrophysical logs, and geochemical properties. This study presents an integrated, physics-informed machine learning workflow for predicting S1 from well logs, mineralogical, and geomechanical data in the upper Shahejie Formation. The dataset comprises 357 S1 core measurements matched to high-resolution well logs (gamma ray, acoustic travel time, density, neutron porosity, and resistivity) over a 799 m stratigraphic interval. To address the inherent depth mismatch between irregularly spaced cores and regularly sampled logs, a constrained nearest-neighbor depth-matching strategy was implemented and validated. Quality control confirmed minimal bias and high precision, ensuring that observed log S1 correlations represent true petrophysical trends rather than alignment-related biases. Physics-informed feature engineering was applied to capture geological ratios, porosity interactions, and depth trends. Interaction terms, including resistivity-TOC combinations, were incorporated to reflect hydrocarbon saturation and organic matter effects. Six ML algorithms were evaluated, including tree-based ensembles, kernel-based methods, and neural networks. The gradient boosting model achieved the best performance, with a correlation coefficient of 0.92 on independent test data and an RMSE of 0.58, representing a 33% improvement over a logs-only baseline. Cross-validation based on unique S1 measurements was used to prevent data leakage and demonstrated stable generalization across the dataset. Feature importance analysis highlights the dominant contribution of physics-informed terms, confirming that physically constrained predictors outperform individual logging or geochemical parameters. The proposed workflow enables continuous S1 profiling with minimal core measurements, supporting reservoir characterization and sweet-spot identification while reducing reliance on expensive geochemical analyses. This study demonstrates how combining rigorous depth alignment, physics-guided feature engineering, and machine learning can deliver reliable continuous S1 prediction for shale energy resources.
How to cite: Bennani, R. and Wang, M.: Physics-Informed Machine Learning Workflow for Free Hydrocarbon Content (S1) Prediction in Organic-Rich Shale Formation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5306, https://doi.org/10.5194/egusphere-egu26-5306, 2026.
With the continuous advancement of oil and gas exploration technologies and associated theoretical frameworks, deep to ultra-deep oil and gas exploration has emerged as a pivotal component of contemporary petroleum geology research and currently seems as a focal area of interest. But, overpressure is prevalent in deep to ultra-deep formations, and there are substantial discrepancies in studies regarding the impact of overpressure on the maturity of hydrocarbon source rocks and hydrocarbon generation. These discrepancies have hindered a comprehensive understanding of hydrocarbon formation and phase states in ultra-deep settings, thereby constraining deep oil and gas exploration endeavors.
The Shawan Sag in the Junggar Basin is characterized by widespread and high-intensity overpressure development, coupled with huge hydrocarbon resources in the lower stratigraphic assemblage. Among these, The Fengcheng Formation, serving as the primary hydrocarbon source rock, is the main source of oil and gas for the reservoirs within the sag. Consequently, this study focuses on the Permian hydrocarbon source rocks in the Shawan Sag of the Junggar Basin as the primary research target. After ascertaining the overpressure development in the Permian strata, typical low-maturity samples were selected to conduct hydrocarbon generation physical simulation experiments under varying pressure conditions. Based on these experiments, maturity evolution and hydrocarbon generation kinetic models that account for pressure were established, and thermal-maturity-hydrocarbon generation evolutionary history simulations were performed for typical wells and a 2D cross-section.
The results reveal the following: (1) There is a negative correlation between vitrinite reflectance and pressure in the vertical direction, with Ro evolution being lower than the normal trend in overpressure zones. (2) Thermal simulation experiments confirm that, under identical temperature conditions, higher pressure leads to a lower equivalent Ro and a greater proportion of medium-to-heavy components in the generated hydrocarbon products, demonstrating the inhibitory effect of pressure on hydrocarbon source rock maturity and hydrocarbon generation products. (3) Based on the results of physical simulation experiments and measured geological data, a 2D thermal-maturity-hydrocarbon generation evolutionary history for the Shawan Sag was simulated. It is concluded that the hydrocarbon source rocks in the Fengcheng Formation of the Shawan Sag are predominantly Type II highly mature hydrocarbon source rocks. The hydrocarbon generation threshold is suppressed until the end of the Triassic, with significant oil generation commencing in the late Jurassic and entering the highly mature stage by the end of the Cretaceous. Regarding hydrocarbon generation products, the cracking of heavy hydrocarbons to generate gas in the Fengcheng Formation is inhibited by overpressure. This study contributes to enhancing the theoretical understanding of overpressure-inhibited hydrocarbon generation and holds practical significance for hydrocarbon exploration in ultra-deep formations within the Shawan Sag.
How to cite: He, B. and Liu, J.: Maturity Evolution History and Hydrocarbon Generation Evolution History of Hydrocarbon Source Rocks in the Fengcheng Formation, Shawan Sag, Under the Influence of Overpressure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6097, https://doi.org/10.5194/egusphere-egu26-6097, 2026.
The high-temperature conditions of deep mining significantly affect the mechanical stability of tar-rich coal. The mechanical properties and energy evolution characteristics of heat-treated tar-rich coal are discussed in this study through experiments and corresponding analyses. The research object is tar-rich coal from the Shaanxi coalfield in China. Microstructural and static/dynamic mechanical tests were conducted on specimens heat-treated at different temperatures (25℃, 200℃, 400℃, and 600℃) to study their structural changes and mechanical behavior. The study shows that tar-rich coal undergoes rapid pyrolysis after 418℃. Therefore, the surface cracks of the coal sample treated at 600℃ deepen, leading to an eight-fold increase in porosity and a permeability as high as 87.1%. The size distribution range of pores and cracks expands, and multifractal characteristics become more pronounced. The carbon composition of the heat-treated tar-rich coal gradually changes from being predominantly aliphatic carbon to being predominantly aromatic carbon. Its surface structure undergoes an evolution from “dense” to “cellular” and then to “fracture-connected”. After static pressure, the failure mode shifts from brittle failure dominated by tension to ductile failure dominated by shear slip and plastic rheology. The energy evolution under different confining pressures exhibits an inherent consistency, with approximately 29% of the input energy dissipated irreversibly. The energy dissipation mechanism under dynamic compressive loading tends towards volumetric fragmentation and shear slip, while the energy in dynamic splitting tests is more concentrated in the generation of through-tensile cracks. This results in the energy absorbed during dynamic compressive failure being 2-3 times that absorbed during dynamic splitting under the same conditions. Overall, temperature significantly affects parameters directly reflecting mechanical properties, while impact pressure influences strength indicators by increasing energy absorption.
How to cite: Meng, F. and Xie, Q.: Study on the structural evolution and mechanical deterioration characteristics of heat-treated tar-rich coal, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7522, https://doi.org/10.5194/egusphere-egu26-7522, 2026.
Reservoir quality in carbonate systems is commonly controlled by secondary porosity associated with fractures and karst. Accurate characterisation of these features is critical for predicting fluid storage and permeability distribution, yet remains challenging using conventional downhole geophysical logging techniques. Interpretation is typically performed manually using resistivity borehole images (BHIs), which resolve rock texture at millimetre scale. However, this approach is time-consuming and yields only a limited and largely qualitative representation of the true porosity distribution, as only a small number of features can be mapped.
To obtain a more comprehensive picture of the macroscopic porosity distribution, we developed a semi-automated workflow for high-resolution pore space mapping and classification in BHIs. We focus on greyscale-converted images rather than raw resistivity data because they are more commonly available for legacy wells. Our workflow applies simple thresholding to generate binary porosity maps from both static (linear conversion of resistivity to brightness) and dynamic images (with histogram equalisation). The dynamic map is grafted onto the static map in areas identified as dark or bright in the blurred static image, resulting in a millimetre-scale porosity map of the borehole wall. Following interpolation between the imager pads and/or flaps, geometric properties are extracted for each connected cluster of mapped pixels, allowing classification of pore types as fractures, vugs, or karst features. The workflow performs well in limestone and dolostone sequences with high resistivity contrast between matrix and pore space, but is less reliable in marly intervals and in sections affected by poor borehole or data quality. We are currently developing an updated, fully automated workflow leveraging machine learning algorithms for pore space segmentation and classification.
As a first application, we analysed BHIs from the North Alpine Foreland Basin in Bavaria, where the Upper Jurassic hosts a hydrothermal reservoir. Of the 16 good-quality BHIs analysed, visual inspection indicates that 13 produced reliable results. By combining the derived macroscopic porosity with available matrix porosity measurements, total porosity can be estimated along the well path. Integration with additional well data enables us to define porosity–permeability trends for active flow zones, elucidate controls on pore space distribution, and derive realistic porosity ranges for reservoir model parameterisation.
How to cite: Bamberg, B., Gajjala, G. R., and Zosseder, K.: Semi-automated porosity mapping in carbonate reservoirs using borehole images, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12538, https://doi.org/10.5194/egusphere-egu26-12538, 2026.
Targeting the extreme downhole environments of oil-rich coal in-situ pyrolysis—characterized by high pressure up to 21MPa, severe corrosion with 3% H₂S content, substantial temperature fluctuations from 120℃ to 650℃, and inherent difficulties in data acquisition—traditional heater control systems suffer from inadequate precision, weak anti-interference capability, poor adaptability, and lack of effective life prediction methodologies for unoperated scenarios. To address these issues, this study conducts in-depth research on an intelligent control system centered on the full-link closed-loop control logic of "perception-decision-execution-feedback".
A novel three-model collaborative decision-making architecture integrating "physical benchmark-condition adaptation-time series supplement" is established. The Weibull model serves as the physical life baseline to ensure compliance with equipment aging laws, reflecting the late-stage accelerated aging characteristic of downhole heaters with a shape parameter greater than 1, a scale parameter representing the characteristic life corresponding to a 63.2% failure probability, and a position parameter defining the minimum safe life threshold. The XGBoost model quantifies the impact of operating conditions such as pressure and corrosion rate through an additive integration mechanism, enabling accurate life correction without relying on the target equipment’s own operating data. The LSTM network captures time-series dynamic anomalies via its gate control unit structure, and its weight is adaptively reduced in unoperated scenarios while the weights of the preceding two models are enhanced through a dynamic weighted fusion approach, addressing the limitation of single-model dependence on operational data.
A hierarchically collaborative control architecture is designed. The perception layer deploys a high-temperature and high-pressure resistant sensor array, achieving 10ms-cycle data transmission through the PROFINET industrial bus and MQTT/OPC UA dual protocols to mitigate environmental interference. The decision layer integrates adaptive fuzzy control with PID regulation, interfaces with a digital twin system for real-time state mapping and fault pre-diagnosis, and embeds a predictive maintenance model based on resistance drift rate and thermal response time. The execution layer takes Siemens PLC as the core, complemented by a thyristor regulator with a response time of less than 10ms and an independent hard-wired safety loop that terminates power supply within 0.5s under extreme conditions. The feedback layer calibrates PID parameters every 10 days and optimizes model weights for full-cycle iterative optimization.
Hardware optimization involves integrating PLC with high-temperature resistant sensors and developing reliable packaging processes including wellhead sealing and cable crossing sealing. Validated by 1200-hour continuous operation on a 205m-deep in-situ test platform, the system achieves life prediction accuracy with a coefficient of determination of no less than 0.9 and a mean absolute percentage error of no more than 10%, controls outlet temperature fluctuation within ±3℃, maintains a control response time of no more than 10ms, an insulation resistance of no less than 100MΩ, and a thermal efficiency of 89.7%. Stable performance is retained even with 30% data loss, providing a systematic theoretical and engineering framework for the safe and efficient operation of oil-rich coal in-situ pyrolysis equipment.
How to cite: Li, Q. and Guo, W.: Multi-field Coupling Precision Control Technology of Downhole Heater for Oil-Rich Coal In-Situ Pyrolysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15511, https://doi.org/10.5194/egusphere-egu26-15511, 2026.
The pore structure of tight reservoirs exhibits significant heterogeneity. Understanding the microscopic distribution and occurrence characteristics of tight oil is crucial for optimizing tight oil resource development. This paper focuses on the Copper Bowl Temple Formation gravel reservoir in the Uersun Sag of the Hailar Basin. Through the use of ultra-thin sections and laser scanning confocal microscopy, the distribution and occurrence characteristics of tight oil components in the reservoir were revealed. By integrating thin-section analysis, SEM, and micro-CT, we systematically analyzed how pore networks influence tight oil occurrence. The results show that the gravel reservoir can be classified into two types: grain-supported and matrix-supported frameworks. The occurrence of tight oil in the reservoir is diverse, mainly manifesting as bound-state star-shaped, particle-adsorbed, semi-bound-state fissure-shaped, and free-state cluster-shaped forms. The pore network in the grain-supported framework reservoir is relatively uniform, with good pore connectivity. Intergranular pores are the primary space for oil and gas accumulation, where tight oil primarily occurs in the free-state cluster-shaped and particle-adsorbed forms. In contrast, the matrix-supported framework reservoir has uneven pore distribution, with numerous isolated pores and poor connectivity. In this type of reservoir, tight oil primarily occurs in the bound-state star-shaped and particle-adsorbed forms, with a small amount occurring in the semi-bound-state fissure-shaped form, restricting the development of tight oil.Cluster-shaped oil in intergranular pores exhibits the highest mobility, spanning the broadest pore size distribution (0.33–7.29 μm), followed by the fissure-shaped and particle-adsorbed forms. Star-shaped oil predominantly occurs in isolated pores with the narrowest pore size range (0.28–4.37 μm).
How to cite: Huang, Y.: Research on the Microscopic Occurrence State Characterization and Influencing Factors of Tight Oil: A Case Study of the Sand and Gravel Reservoir in the Hailar Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15592, https://doi.org/10.5194/egusphere-egu26-15592, 2026.
Understanding the mechanisms of hydrocarbon migration, accumulation, and alteration, particularly how evolution controls these processes, is critical for exploring lithologic hydrocarbons in reservoirs. In the complex tectonic settings of the continental margin of the stable North China Craton, there is a significant presence of small yet highly prolific hydrocarbon reservoirs. The processes of hydrocarbon migration and accumulation are complex and thus represent an important research focus in geology. This study, based on core, logging, and seismic data and integrating fluid inclusion analysis, quantitative fluorescence techniques, and geochemical experiments, combines the shale smear factor and paleotectonic reconstructions to clarify the hydrocarbon accumulation episodes, migration pathways, and factors controlling reservoir adjustments in the Yanwu area of the Tianhuan Depression in the Ordos Basin, China. The results reveal three types of NE-trending left-lateral strike-slip faults: linear, left-stepping, and right-stepping. Shale Smear Factor (SSF) analysis confirms that these faults exhibit segmented opening behaviors, with SSF > 1.7 identified as the threshold for fault openness. Multiparameter geochemical tracing based on terpanes and steranes shows that lateral migration along fault zones dominates the preferential migration pathways for hydrocarbons. Fluid inclusion thermometry revealed homogenization temperatures within the 100–110°C and 80–90°C intervals, while the oil inclusions exhibit blue or blue-and-white fluorescence, reflecting early hydrocarbon charging and late-stage secondary migration. Integrated analysis indicates that during the late Early Cretaceous (105–90 Ma), hydrocarbons were charged upward through open segments of linear strike-slip fault zones in the northern study area, experiencing lateral migration and accumulation along high-permeability sand bodies and unconformities in the shallow strata. Since the Late Cretaceous (65 Ma–present), the regional tectonic framework has evolved from a west-high, east-low to a west-low, east-high configuration, inducing secondary hydrocarbon migration and leading to the remigration or even destruction of early-formed oil reservoirs. This study systematically demonstrates that fault activity and tectonic evolution control the accumulation and distribution of hydrocarbons in the region. These findings provide theoretical insights for hydrocarbon exploration in regions with complex tectonic evolution within stable cratonic basins.
How to cite: Yang, Z.: Influencing factors of hydrocarbon migration and adjustment at the edge of a stable cratonic basin: Implications from fluid inclusions, quantitative fluorescence techniques, and geochemical tracing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15641, https://doi.org/10.5194/egusphere-egu26-15641, 2026.
The reservoir of Qinhuangdao 32-6 oilfield is a complex fluvial sedimentation, with large lateral variations in sand bodies, complex oil-water relationships, and diverse reservoir types. According to its sedimentary characteristics, the sedimentary facies of the oilfield can be further divided into two types: braided river and meandering river. The level of channel sand body configuration interface, configuration units, and their combinations are not yet clear; There is still a lack of understanding on how configuration units and their combinations under different levels of configuration interface control can control reservoir heterogeneity, which makes it difficult to predict the gas content inside individual sand bodies in the study area.
In response to the above issues, under the constraint of the configuration interface level, combined with the lithology and lithofacies of sedimentary microfacies units and their combination types, the configuration interface of the study area is divided. Based on the vertical sequence sedimentary characteristics of the configuration unit combination, the configuration unit combination is further divided, and the control effect of configuration on reservoir heterogeneity under different levels of interface control is clarified. Among them, the 5-level configuration interface controls the reservoir plane heterogeneity, which is controlled by the rise of the reference plane and structural subsidence; The level 4 configuration interface controls the heterogeneity between reservoir layers, which is controlled by terrain slope and erosion; The 3-level configuration interface controls the heterogeneity within the reservoir layer, which is controlled by hydrodynamic conditions, channel curvature, channel migration degree, sedimentary load, flow rate, and diagenesis. Finally, a control mode for reservoir heterogeneity under 3-5 level interface constraints was established.
How to cite: li, S.: Heterogeneous characterization of reservoirs at different levels and types of rivers---Taking the Neogene Reservoir of Qinhuangdao 32-6 Oilfield as an Example, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16087, https://doi.org/10.5194/egusphere-egu26-16087, 2026.
Quantitative evaluation of source rock thermal maturity is a core component of petroleum system analysis. Traditional deterministic modeling methods are affected by geological parameter uncertainties, making it difficult to meet the demands of shale oil and gas sweet spot prediction. Taking the Permian source rocks of the Junggar Basin as the research object, this paper constructs a thermal evolution surrogate model integrating 3D convolution and spatial attention mechanism, and adopts the Unscented Kalman Inversion method to realize key parameter inversion and uncertainty quantification. Thermal history uncertainty propagation is accomplished via Monte Carlo sampling. Simulation results show that this method can efficiently improve the accuracy of source rock thermal maturity evaluation. The Permian source rocks have generally entered the oil generation stage, with the sag centers reaching the high-maturity gas generation stage, which is consistent with drilling measured data. This method provides a new paradigm for uncertainty modeling of petroliferous basins and has important guiding significance for hydrocarbon exploration.
How to cite: Xu, B., Lei, Y., Zhang, L., and Liu, N.: Uncertainty Analysis Method for Petroleum System Modeling Based on SurrogateModel to Improve Thermal Maturity Evaluation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21757, https://doi.org/10.5194/egusphere-egu26-21757, 2026.
Posters virtual: Tue, 5 May, 14:00–18:00 | vPoster spot 4
EGU26-6953 | ECS | Posters virtual | VPS19
Development of Organic Pores in the Permian Gufeng Formation Shale, Northern Sichuan Basin： Combined Effects of Bio-precursor, Pore Filling, and Mineral-Organic InteractionsTue, 05 May, 14:06–14:09 (CEST) vPoster spot 4