Confronted with the challenges of ever‐increasing global demand for oil and gas, coupled with the depletion of conventional resources, the strategic importance of unconventional oil and gas resources is becoming increasingly significant, with shale oil being particularly crucial. Immature to low‐maturity shale oil reserves are extremely abundant, constituting over 80% of the world’s total shale oil resources. Thus, the efficient enhancement and development of immature to low‐mature shale oil is of profound importance for ensuring future energy supplies and reshaping the global energy landscape. This review begins with an in‐depth analysis of the microscopic conversion mechanism and reaction pathway of immature to low‐maturity shale oil at the molecular structural level. Building on this foundation, it systematically summarizes and analyzes the current main in situ upgrading methods, including thermal upgrading and catalytic synergistic thermal upgrading combined with catalysts, which essentially rely on heat to drive the thermal cracking and hydrogenation reactions of organic matter. However, these methods typically encounter challenges such as high energy consumption, elevated costs, and substantial environmental impacts, which limit their widespread adoption and application. In contrast, microbial upgrading technology exhibits significant advantages by achieving upgrading through environmentally friendly and low‐energy biological processes. The primary mechanisms include direct biological conversion, where microorganisms directly metabolize organic components in shale, degrading or converting them into lighter hydrocarbons with improved mobility and lower viscosity, and indirect biological promotion, which alters the properties of reservoir rocks, thereby promoting the release of organic matter and enhancing its effective contact with the external modification environment. Although the microbial upgrading of immature shale oil remains in its foundational development stage, lacking in mechanistic and systematic research, existing studies have demonstrated progress in the application of microbial technology for shale oil extraction. This progress is achieved through the screening and optimization of microbial communities to enhance shale oil recovery rates. Consequently, this review explores the future development directions of microbial technology in the field of shale oil and gas extraction in its final section, aiming to promote the widespread application of this green and low‐carbon technology.
Production forecasting for oil and gas wells is a decisive element of field‐development planning because it directly guides recovery strategy design, production optimisation and risk management. Conventional methods, including empirical decline‐curve analysis (DCA) and full‐physics numerical simulation, are limited either by their inability to capture complex non‐linear flow behaviour or by prohibitive computational requirements. The rise of big data and artificial intelligence has introduced machine learning models such as support vector regression (SVR), random forests (RFs), XGBoost and multi‐layer perceptrons (MLPs), whose efficient non‐linear fitting has improved predictive accuracy; however, their black‐box nature and weak physical consistency now constrain further progress. Modern deep learning (DL) architectures—including long short‐term memory (LSTM) or gated recurrent unit (GRU) networks, CNN–LSTM hybrids, transformers, graph convolutional networks (GCNs) and kernel adaptive networks—extend modelling capability to long temporal sequences and systems with multiple interacting wells, fostering a technical shift from purely data‐driven learning toward physics‐enhanced intelligence. Of particular note, physics‐informed neural networks (PINNs) embed Darcy flow equations and related constraints directly in the loss function, which markedly strengthens extrapolation ability and interpretability while offering efficient support for history matching, surrogate modelling and closed‐loop reservoir management (CLRM). Nevertheless, these networks still face challenges involving the balance of loss‐term weights, multi‐scale coupling and training convergence; progress will rely on dynamic weighting schemes and a standardised library of physical priors. This review, therefore, synthesises the evolution from traditional machine learning to physics‐constrained approaches in production forecasting, assesses their respective advantages and limitations and identifies future research priorities in high‐quality dataset construction, cross‐field transfer learning, interpretability enhancement and system‐level intelligent optimisation in order to realise fully digital and closed‐loop intelligent oilfields.
Asphaltene precipitation frequently occurs in oil wells within the Tuoputai area of the Tarim Basin, significantly hindering production efficiency. In addition to external factors, such as temperature and pressure, the effects of geological factors on asphaltene precipitation warrant further investigation. Base on previous studies, this article examines the geological controls on asphaltene precipitation by analyzing the spatial distribution of precipitation wells, the physical properties and group composition characteristics of crude oils, and their charging histories. The results show that wells experiencing asphaltene precipitation are mainly distributed near NNE‐trending main and secondary faults, where rapid variations in oil physical properties are observed. The faults act as vertical migration and charging pathways that facilitate the mixing of crude oils within the reservoir. The content of resin and asphaltene in the crude oils from the asphaltene precipitation wells was low, the instability coefficient (CⅡ) was high, and the stability of the crude oils system is unstable. In the vicinity of the faults, the crude oils charged during the late Hercynian and Himalayan periods, with obvious differences in physical properties and maturity, were mixed in the reservoir, and the mixing effect was obvious, and the stability of the crude oils system was damaged, which may be an important factor affecting the occurrence of asphaltene precipitation. The findings of this study provide critical insights into the mechanisms of asphaltene precipitation and have important implications for the efficient production and reservoir management.
Gas‐in‐place (GIP) content is a critical indicator for evaluating deep coal/shale resource potential, typically categorized into lost gas content, desorbed gas content, and residual gas content. The lost gas content cannot be directly quantified and requires specific methods for assessment. Current lost gas content restoration methods exhibit significant discrepancies between estimated results and pressure‐holding coring measured values, yet the underlying causes of these errors remain not fully understood, which hinders the effective refinement of these methodologies. Study conducted field degassing experiments on shales from the Longmaxi Formation in the Sichuan Basin and coals from the Taiyuan and Shanxi Formations in the Ordos Basin (a total of 12 samples, including four pressure‐holding coring samples). We systematically compared and analyzed the Amoco curve fit method (ACF) and modified curve fit method (MCF) methods using experimental and numerical simulation results. The issue of excessive overestimation of lost gas content has been addressed through method improvements. The applicability of the improved method and the rationale behind parameter selection have been thoroughly discussed. The study reveals that: (1) The primary reason for the significant errors in the ACF and MCF methods is the neglect of the infinite series summation term in practical applications, which affects the lost gas content calculation and results in generally overestimated values. (2) A selection criterion for order n was established for the improved ACF and MCF methods. For deep coalbed methane (CBM) applications, the optimal order is n = 5 for the improved ACF method and n = 10 for the improved MCF method. When applied to deep shale gas, an optimal order of n = 20 is more appropriate for the improved ACF method, whereas the MCF method fails to effectively restore lost gas content in deep shale gas reservoirs. (3) Comparative analysis of the improved methods revealed that the improved MCF method demonstrates superior adaptability for lost gas content restoration in deep CBM, while the improved ACF method exhibits stronger applicability in deep shale gas. Validation using pressure‐holding coring data from deep shale samples demonstrated that the improved methods significantly enhanced calculation accuracy, reducing error ratios from 276.31%, 164.06%, 189.70%, and 365.55% to 1.41%, 46.58%, 45.49%, and 34.59%, respectively, compared to conventional methods. This study holds significant implications for resource potential evaluation, sweet spot selection, and development plan optimization of deep coal/shale gas.
Information on the spatial variation of solar radiation is essential for sustainable solar energy planning. This paper models average monthly and annual solar radiation across Zimbabwe using a 30 m Shuttle Radar Topographic Mission (SRTM) digital elevation model (DEM). The spatial analyst tool was used to compute solar radiation from DEM for specific areas based on their potential for hosting solar plants. Multiple statistical model evaluation metrics namely Pearson correlation ( R ), coefficient of determination ( R 2 ), mean absolute error (MAE), root mean square error (RMSE), standard deviation of residual (SD) and Willmott’s index of agreement (WIA) were computed to validate the performance DEM derived radiation and National Aeronautics and Space Administration–Prediction of Worldwide Energy Resources (NASA‐POWER) data against ground radiation measurements. The study further developed regression equations for respective areas across the country. Results show that modelled radiation was highly and positively correlated with measured radiation ( R > 0.71, RMSE < 0.5 kWh/m 2 and MAE < 0.7 kWh/m 2 ). Furthermore, results illustrates that Zimbabwe has high potential for solar energy with an annual average radiation ranging between 4.6 and 6.6 kWh/m 2 . The study demonstrates the increasing role of geospatial analysis in solar energy planning.
Understanding pore structure and methane sorption (MS) in shale gas reservoirs is critical for accurately estimating gas-in-place and prospective natural gas resources. The Longmaxi Shale, a leading formation for deep shale gas development in China, faces challenges in its economic production due to its strong spatial heterogeneity, complex pore structure, and poorly characterized methane adsorption volume. In this study, six core samples collected from the Da’an area, Chongqing Municipality, were analyzed to determine lithology, pore structure, and water vapor adsorption by using integrated approaches of X-ray diffraction (XRD), total organic carbon (TOC) quantification, microscopy, μ-X-ray fluorescence (μ-XRF), mercury intrusion porosimetry (MIP), N 2 physisorption (NP) and CO 2 physisorption (CP), and MS. A specialized sampling workflow was designed to mitigate spatial heterogeneity effects. The results indicate that the samples comprise argillaceous-siliceous mudstone, clay-rich siliceous mudstone, and mixed siliceous mudstone. Porosity ranges from 1.88% to 2.84%, specific surface area changes between 20.1 and 31.5 m 2 /g, and absolute MS capacity varies between 1.88 and 3.19 m 3 /t. TOC and pore size are the two major controlling factors of MS. These findings advance mechanistic understanding of pore structure and MS in shale, offering insights for optimizing production in shale reservoirs.
With the global surge in oil consumption, chemical flooding has gained prominence, leading to the development of advanced systems such as alkali–surfactant–polymer (ASP) and salt–surfactant–polymer (SSP) flooding. However, current research on surfactants for chemical flooding predominantly focuses on enhancing interfacial tension (IFT) reduction, resulting in inadequate emulsification capacity for heterogeneous and heavy oil reservoirs. Building on recent research advancements in the mechanisms of emulsification for enhanced oil recovery (EOR), this review systematically examines the distinctions and contributions between IFT reduction and emulsification effects during oil displacement processes. The formation mechanisms of emulsions are analyzed from both microscopic and molecular perspectives, with further discussions on subsequent mechanisms including micellar solubilization and spontaneous emulsification reported in existing studies. Furthermore, the seepage characteristics of emulsions are critically reviewed from both microscopic and macroscopic viewpoints, offering a comprehensive analysis of their flow behaviors in porous media as documented in the literature. Additionally, this work provides an in-depth analysis of the physicochemical properties, oil displacement behaviors, and molecular architectures of advanced surfactants exhibiting high emulsifying efficacy. Special attention is given to the functional group interactions within surfactant molecular structures. Comparative assessments reveal that incorporating polyoxyethylene, polyoxypropylene (PO), and aromatic moieties significantly improves hydrophilic–lipophilic balance (HLB) and emulsion stability. These findings provide actionable insights for designing next-generation surfactants with optimized emulsification performance.
Large-scale carbon capture and storage (CCS) is essential for reducing CO 2 emissions, and Denmark’s initial efforts targeted depleted oil fields in the outer North Sea. More recently, focus has shifted to saline aquifers located outside the established North Sea oil province. Unlike hydrocarbon (HC)-bearing reservoirs, saline aquifers do not pose risks of reservoir clogging from heavy oil residues or unintended HC migration and pollution beyond the storage structure. The Jammerbugt structure, situated in eastern Skagerrak beyond the oil province, remains undrilled but is located in a unique geological setting where an active petroleum system has been speculated. This study aims to de-risk the presence of petroleum in the Jammerbugt structure by applying basin and petroleum system modelling (BPSM). The model is calibrated to actual vitrinite reflectance (VR) data to constrain the tectonic and geothermal history of the area, that is, the thermal history is constrained by the measured %VR o values and their quantified uncertainties. The overall calibration is evaluated through calculated root mean squared (RMS) errors, which shows good performance within the potential kitchen area, and a less good performance along the model margins. A two-case scenario was developed to test the generation and migration of petroleum from the Lower Jurassic Fjerritslev Formation (Fm) into the Jammerbugt structure: A best-fit (BF) and a high-end (HE) cases. The BF case represents the most likely geological conditions, that is, the burial depth, timing and magnitude of uplift and exhumation and paleo heatflow, and applying a four-phase petroleum kinetics model. The HE case incorporates the upper bounds for these variables, constrained by the uncertainties, to create a “what-if” scenario together with a conventional two-phase petroleum kinetics model. Both the BF and the HE scenarios indicated the potential presence of a working petroleum system within the Fjerritslev Trough; however, petroleum was not expelled from the source rock (Fjerritslev Fm) in either of the scenarios, due to poor source rock quality. The findings of this study de-risk expulsion of petroleum from a working petroleum system into the Jammerbugt structure and in the Skagerrak region in general, emphasising the Jammerbugt structure as a future potential CCS candidate.
The complexity of internal architecture within thick sandstone bodies is a key geological factor controlling fluid distribution in reservoirs and influencing hydrocarbon recovery efficiency. To investigate the strong sandbody heterogeneity and complex fluid distribution in the Sangtamu area of the Tabei uplift, Tarim basin, this study focuses on the Triassic TI sublayer. Integrated analysis of core observations, well-logging data, and 3D seismic data confirms the TI sublayer as a braided fluvial depositional system. Based on the spatial distribution patterns of fourth-order architectural units within this braided fluvial reservoir, a detailed reservoir characterization study was conducted: identifying individual channel stories within single wells utilizing calcareous and argillaceous interbeds, delineating single-phase braided channel belts using a well-to-well correlation method constrained by paleotopographic elevation, and systematically dissecting the internal architectural characteristics of the amalgamated sand body according to a hierarchical framework (braided channel belt, single channel, internal architectural elements within a single channel). Results shows that, lateral migration of channels resulted in the stacking of sandstone body from different layers. Within coeval channel belts, architectural boundaries between different single channels, as well as between mid-channel bar sand body and channel-fill sandstone body within individual channels, impeded sandbody connectivity (resulting in incomplete connectivity). This research effectively clarified the oil–water distribution relationships and resolved static geological conflicts within the study area, providing a robust geological basis for optimizing field development plans and enhancing hydrocarbon recovery.
In order to clarify the action mechanism of surfactants on the waxing layer of crude oil pipeline under the action of asphaltene, this article explores the effects of five surfactants, sodium dodecyl benzene sulfonate, sodium fatty alcohol polyoxyethylene ether sulfate, hexadecyltrimethylammonium chloride, Tween-80, and Span-80, on wax removal rate under the combined action of asphaltene using a newly constructed dynamic experimental apparatus. It is found that Tween-80 and Span-80 surfactants had a better wax removal effect. Therefore, the two surfactants, Tween-80 and Span-80, are selected for 1:1, 1:2 and 2:1 compounding experiments. When the compounding ratio of the two surfactants is 1:1, the wax removal rate is higher; Span-80, the surfactant with the highest wax removal rate, is chosen to investigate the wax removal law when the cold finger wall temperature is changing in the range of 0–25°C. It is found that the rate of wax removal increased with the increase of cold finger wall temperature and wax removal medium temperature. When the number of revolutions increases, the flow rate of hot water in the rotating cylinder also increases, the shear force on the wax layer also increases, and the wax removal rate increases under the joint action of asphaltene and Span-80. This study is of guiding significance for engineering practice.
The formulation of drilling fluids with the desired characteristics required to achieve a successful drilling operation depends largely on the drilling additives. In this study, we investigated the potential of two agrowastes, wheat husks (WHs) and periwinkle shells (PSs) as additives in water-based drilling fluids (WBFs). The experimental study was conducted according to API RP 13B-1 standard procedure at ambient condition. A comparative study was conducted between a reference fluid (RF) formulated with 2.0 g carboxymethyl cellulose (CMC) and six additional samples formulated with varying concentrations of the additives alone and in combination with CMC. PS slightly enhanced pH and mud weight (MW) better than WH. The combination of the additives with CMC in the ratio 1:10 as in E and F yielded the best samples with rheological properties closest to the RF (A). Sample A yielded a filtrate loss of 8.50 mls, while both D and E formulated with WH and CMC yielded the best comparable volume of 10.90 mls and same cake thickness of 0.05 mm. At an annular velocity of 40 ft/min, Sample A showed the best carrying capacity with a cuttings carrying index (CCI) of 0.97. Samples C, E, F, and G gave CCI values in the range of 0.43–0.54. B yielded a very poor CCI of 0.04, while D gave a very high CCI of 2.49 above the acceptable range of 1.0–1.5. An increase in the concentration of the additives increased most of the mud properties, while aging reduced it. The Herschel–Bulkey and Sisko models fit the drilling fluids better than the two-parameter models. The cost of WH and PS were found to be lower than that of CMC by 97.5% and 99.8%, respectively. A barrel of D and E also cost less by 2.6% and 3.04%, respectively. Analysis of carrying capacity is recommended to ensure additives not only improve the targeted properties but also produce muds with good hole cleaning features. Utilizing agrowastes as additives for improved drilling fluid performance saves costs and reduces the volume of wastes and their environmental impact.
Oil-contaminated sludge is a common hazardous solid waste produced by the petrochemical sector. Traditional separation systems demonstrate low separation efficiency and high treatment costs, leading to ineffective disposal of oil sludge. This work intends to address the difficulties of low efficiency, high energy consumption, and secondary pollution associated with standard treatment procedures by enhancing the treatment effect of nanoemulsions in oil sludge treatment. A nanoemulsion, principally constituted of the biological surfactant rhamnolipid, was created utilizing the phase inversion approach. Its particle size, zeta potential, oil–water interfacial tension (IFT), and stability were extensively investigated. The results indicated that the nanoemulsion had a tiny particle size (134.6 ± 2.1 nm), a high zeta potential absolute value (>30 mV), and an ultralow oil–water IFT (0.15 mN/m), indicating exceptional physical stability and oil removal capabilities. Through single-factor studies to optimize processing parameters, the ideal circumstances were established as follows: 20 mL of nanoemulsion diluted 100 times, a reaction temperature of 35°C, a reaction duration of 60 min, a centrifugal speed of 4500 rpm, and a centrifugal time of 15 min. Under these conditions, the residual oil content of the oil-contaminated sludge was reduced by 10% from 12.13% to 2.13%, greatly surpassing typical chemical treatment procedures. This study provides a theoretical basis and technical support for the green and efficient treatment of oil-contaminated sludge, carrying substantial implications for fostering sustainable growth in the petrochemical industry.
To clarify the micropore structure characteristics of shales in the second member of the Funing Formation, Subei Basin and their influence on shale oil occurrence, various tests were conducted, including low‐temperature nitrogen adsorption (LTNA), scanning electron microscopy (SEM), rock pyrolysis, total organic carbon (TOC), and X‐ray diffraction (XRD) analysis. The organic matter, mineral compositions, and oil content of the shales were analyzed and the micropore structure and fractal characteristics were clarified. Additionally, factors influencing shale oil occurrence were disclosed. The results reveal that the mineral compositions of the studied shales are complex, comprising quartz, clay minerals, calcite, and dolomite. Pores at the edges of brittle mineral particles predominate. The LTNA curve exhibits an H2–H3 type, corresponding to a high specific surface area (SSA) and a low average pore size. Micropores (<25.00 nm) dominate, contributing significantly to the total pore volume (PV) and SSA. The pore size distributions (PSDs) are unimodal, peaking at approximately 3.00 nm. Fractal analysis identifies two stages, with fractal dimensions D 1 ranging from 2.46 to 2.58 (mean 2.53) and D 2 from 2.52 to 2.83 (mean 2.75). Pore structure and fractal dimensions are controlled by mineral compositions and organic matter. Higher quartz, calcite, and organic matter contents promote larger average pore sizes and lower fractal dimensions, indicating more homogeneous pore structures. Larger average pore sizes and simpler pore structures enhance free oil accumulation and production. Shales with TOC > 2.30% in the Funing Formation are most favorable for shale oil exploration and development. These findings provide insights for optimizing shale oil exploration in the Funing Formation, aiding the understanding of micropore structures and their role in oil accumulation.
Process‐based geological modeling replicates the physical laws governing depositional and diagenetic processes, generating geologically realistic models. However, these models sometimes fail to align with well log, seismic, and other spatial data. Conditioning process–based geological models to such data is essential, but has posed challenges for decades. Traditional conditioning methods involve trial‐and‐error or automated inverse procedures to fine‐tune input parameters. While these methods can enhance model calibration, they often fall short of achieving fully satisfactory results. This paper introduces a novel approach that integrates a multiscale regionalized (MR) multiple‐point statistics (MPSs) method with process‐based geological modeling to improve well data conditioning. The proposed workflow, termed MPS‐MR, leverages statistical inference of geological patterns derived from replicated events within localized regions of a training image (TI). During stochastic simulation, each unsampled location is associated with a localized region of the TI. As these regions are location‐dependent, the MPS‐MR method overcomes the stationarity requirement of the TI, a limitation of many existing MPS techniques. The MPS‐MR captures and reproduces geological patterns and trends across multiple scales. Its integration with process‐based modeling offers an effective solution for well data conditioning, while preserving geological patterns and trends. This is demonstrated through a case study involving high‐sinuosity fluvial channel modeling.
Nonhydrocarbon gases are significant components of natural gas, and their concentration levels are crucial factors affecting reservoir development value. While explorations have progressively moved from shallow to deep and now ultradeep reservoirs, research on the geochemical characteristics of nonhydrocarbon gases in such extreme depths remains limited, leaving their origins and types poorly understood. This paper analyzes the geochemical characteristics and origins of ultradeep nonhydrocarbon gases (CO 2 , H 2 S, N 2 , He, and H 2 ) across major global basins to determine their origins. CO 2 concentrations reach up to ~40% but are generally below ~15%. The concentration increases with depth, primarily due to inorganic origins, with thermochemical sulfate reduction (TSR) and magmatic CO 2 being the main causes. Depths are mainly between 6000 and 7100 m. N 2 concentrations peak at ~26% but are generally below ~6%. It mainly originates from crustal sources and the high‐temperature cracking of sedimentary organic matter during postmature. Depths are mainly between 6000 and 7100 m. H 2 concentrations reach up to ~1.6% but are generally below ~0.2%. It is concentrated at depths between 7100 and 7800 m and may primarily have a biological origin. He concentrations are generally below ~0.07% and are mainly found at depths between 6000 and 7700 m. The concentrations fall well short of the commercial threshold (0.1%), indicating limited potential for He enrichment in ultradeep reservoirs. H 2 S concentrations reach up to 46% but are generally below 10%. The concentration slightly increases with depth, mainly due to TSR processes. Depths are primarily between 6000 and ~7600 m. Understanding these common and varying patterns of nonhydrocarbon gases may provide theoretical guidance for future exploration targets in ultradeep nonhydrocarbon gases like He and H 2 .
Carbonate reservoirs host significant hydrocarbon, groundwater, geothermal and CO 2 ‐ and H 2 ‐storage resources. However, their complex depositional, tectonic and diagenetic histories make it challenging to efficiently characterize and predict their flow behavior. Here, we use a novel, rapid and efficient screening methodology that integrates experimental design, the construction of three‐dimensional (3D) reservoir models via sketch‐based methods and single‐phase flow diagnostics to investigate the impact of geological heterogeneity on flow patterns and displacement in an ultra‐deep (>7 km) carbonate reservoir in the north‐central Tarim Basin, northwest China. Eight heterogeneities are investigated: (1) strike‐slip fault zone width; (2) complexity of flower structure configuration; (3) continuity of fault core lithology; fault zone rock properties related to (4) karstification and (5) late, post‐karstification cementation; (6) the occurrence of fault‐perpendicular fracture corridors; (7) connectivity of fracture corridors to fault zones and (8) variability in host rock porosity and permeability. Fault zone width has the most significant impact on reservoir properties, with wider fault zones increasing effective horizontal permeability along fault zone strike. Fracture corridor occurrence and connectivity to the fault zone are the principal heterogeneities controlling effective permeability perpendicular to fault zone strike. Fault zone rock properties reflecting karstification and late cementation also significantly impact effective permeability in all directions. Other heterogeneities have little effect on effective permeability and well performance. However, simulated wells in negative flower structures and the main fault zone have higher productivities on average than simulated wells in positive flower structures and the host rock, similar to published production data from the ultra‐deep reservoir. This study demonstrates the value of the screening methodology for assessing the effects of uncertainty in the interpretation of geological heterogeneities in complex carbonate reservoirs, in order to narrow the focus of future, more comprehensive reservoir simulations. The screening methodology is directly transferable to low‐carbon energy applications in settings with sparse data.
The world is running out of time to be on target for the Paris Agreement to maintain an average global temperature rise of 1.5°C. Carbon capture and storage (CCS) can win the race to anthropogenic gas stabilisation. Characterisation of geological formations is fundamental to ascertain the ability to keep injected carbon in perpetuity without posing a risk to the environment. This study focuses on the characterisation of the mineralogy, petrophysical, petrographic properties and micromorphological data of reservoirs using core samples from the reservoirs in the Niger Delta, Nigeria. A systematic set of specialised equipment such as XRD, X‐ray fluorescence (XRF) and SEM‐EDS was implored to understand the preliminary characterisation of selected reservoirs before carbon dioxide injection. Porosity and permeability were measured using a helium porosimeter to complement the mineralogical composition and morphology. The petrographic and mineralogical characteristics of the core samples provide crucial insights into potential geochemical reactions. Quartz, orthoclase and albite were found to be dominant in all the sampled depo belts with chlorite and garnet being the trace minerals. The sampled depo belts recorded an average porosity of 10% to 30% with permeability averaging 130–300 mD, which surpass the cautionary indicator limits. The findings indicated a positive potential for CCS in the Niger Delta with suitable mineralogical and petrophysical properties. The positive findings of this research pave the way for pilot testing with the physical injection of carbon dioxide. They also set a pathway for enacting and implementing carbon dioxide mitigation guidelines controlling CCS installations by the Nigerian Upstream Petroleum Regulatory Commission (NUPRC).
Raman spectroscopy has shown considerable potential in the study of organic macerals in source rocks due to its significant benefits of accuracy, efficiency, and in situ nondestructive detection. This technology successfully applies to the reconstruction of paleotemperature and pressure environments, the quantitative evaluation of organic matter maturity, and the construction of a carbon Raman spectroscopy geothermometer model. The present study systematically examines the intrinsic relationship and the application between Raman parameters and material composition and molecular structure, as well as the application, challenges, and future directions of Raman spectroscopy in the current research field of source rock evaluation.
The Potwar Plateau region of the Upper Indus Basin in Pakistan is known for its complex carbonate reservoirs, which pose significant challenges for hydrocarbon exploration and production. The integrated reservoir simulation study can help mitigate these challenges by better understanding the reservoir behavior and optimizing production strategies. The reservoir characterization of this region has essential importance in Pakistan because tight limestone and fractures (with vugs and leached features) may provide a zone of high porosity, permeability, and reservoir properties with isolated distribution in tight carbonates. The seismic and well log data were integrated to get the reservoir characterization and mark targeted reservoirs (Chorgali and Sakesar Formations) in Balkassar Oil Field. The study utilized 3D seismic interpretation, petrophysics analysis, rock physics analysis, and seismic inversion techniques to evaluate the subsurface properties of the carbonate reservoir. The time grid and depth contour map generation for Chorgali and Sakesar Formations show less time, about 1.2–1.3 s for Chorgali and 1.32–1.488 s for Sakesar which reveal clearly that the central part between the two faults is a shallow portion which is the crest of Balkassar anticline forming the suitable structural trap for hydrocarbon accumulation. Three reservoir zones with certain depths are marked based on petrophysics and rock physics analysis. The cross‐plot between mu–rho versus lambda–rho value indicates a high porosity value at 2,460–2,580 m. From seismic inversion, low impedance values are observed in that reservoir zone (2,400–2,500 m).
Geothermal energy is a green and sustainable energy source. Rational development and utilization of geothermal energy can not only improve the living environment for local residents but also reduce environmental pollution and promote sustainable economic development. Based on the thermal physical parameters and lithologic parameters, the volume method was implemented to comprehensively evaluate the thermal reservoir temperature, geothermal resource types, and resource potential of the Cenozoic Minghuazhen Formation, Guantao Formation, and Dongying Formations in the Dongpu Depression. The natural breakpoint method has been applied to categorize the resource intensity in the Dongpu Depression, thus clarifying the distribution of geothermal resources and favorable development areas in the study area. The results show that the reservoir temperature of the Minghuazhen Formation of the Dongpu Depression is 40–58°C, while the reservoir temperatures of the Guantao and Dongying Formations are 70–112°C and 70–140°C, respectively, primarily harboring medium–low‐temperature geothermal resources. Through calculation, it is found that the geothermal resources of the Cenozoic Minghuazhen, Guantao, and Dongying Formations in the Dongpu Depression are 3.70 × 1020 J, 2.23 × 1020 J, and 2.30 × 1020 J, respectively. Collectively, these amount to a total of 8.23 × 1020 J, equivalent to approximately 281.29 billion tons of standard coal. A comparative study of the calculated results of the three geothermal reservoirs in the research area reveals that the Dongying Formation exhibits the highest potential for geothermal resource exploration, particularly in the eastern Changyuan Sag and the Xuji Uplift. The Minghuazhen Formation follows closely. Notably, the geothermal resource potential is significant in the Gaopingji Slope, the East Changyuan Sag, the Xuji Uplift, and the Machang Uplift in the southwest. While the Guantao Formation has a relatively smaller potential, the eastern depression of the Changyuan and the middle section of the Xuji Fault, near the Yellow River Fault, do possess a certain degree of exploration value. The research can provide important basic support for the design of geothermal development in the Cenozoic of the Dongpu Depression.
