Reservoir Geological Model Research Articles

A New Approach to a Fracturing Sweet Spot Evaluation Method Based on Combined Weight Coefficient Method—A Case Study in the BZ Oilfield, China

The Sha3 member of the BZ Oilfield in Bohai Sea represents a typical ultra-low permeability thin interbedding reservoir. Hydraulic fracturing is an effective method for increasing oil and gas production. However, the complex geological conditions make it difficult to screen out the optimal frac spot. Consequently, the design of hydraulic fracturing exhibits certain limitations. A novel method for evaluating sweet spots is proposed, based on a refined geological reservoir model that considers the varying degrees of influence that geological and engineering factors have on fracturing effectiveness. This method utilizes grey correlation and hierarchical analysis to quantify and characterize the weight coefficients of each factor, ultimately leading to a combined weight coefficient approach. The results indicate that permeability and fracturing scale are the primary factors that impact the post-frac production of the BZ oilfield, with their respective combined weights being 0.33 and 0.25. The average weight for geological factors is 0.18, while for engineering factors it is 0.15. This suggests that geological factors have a greater influence on production than engineering factors. Furthermore, the correlation coefficient between the dual sweet spot index and the production is 0.96, indicating a strong positive correlation between the two variables. After comparing the predicted and actual production of each well, it was determined that the anastomosis rate is 80%. This finding holds significant guiding significance for selecting the optimal fracturing spot.

Research on Inter-Fracture Gas Flooding for Horizontal Wells in Changqing Yuan 284 Tight Oil Reservoir

In tight reservoir development, traditional enhanced oil recovery (EOR) methods are incapable of effectively improving oil recovery in tight reservoirs. Given this, inter-fracture flooding is proposed as a new EOR method, and physical model simulation and numerical simulation are performed for inter-fracture water flooding. Compared with inter-fracture water flooding, inter-fracture gas flooding has a higher application prospect. However, few studies on inter-fracture gas flooding have been reported, and its EOR mechanisms and performance are unclear. This paper used the geological model of the actual tight reservoir to carry out numerical simulations for two horizontal wells in the Changqing Yuan 284 block. The results showed that (1) inter-fracture gas flooding can effectively supplement formation energy and increase formation pressure; (2) inter-fracture gas flooding delivers simultaneous displacement, which can effectively increase the swept area in tight reservoirs; (3) injected CO2 dissolves into the reservoir fluid, reduces fluid viscosity, and improves fluid flow through the reservoir; and (4) the recovery factor increment of the CO2 injection is higher than those of natural gas injection and N2 injection. The findings of this research provide references for the production and development of tight reservoirs.

Application of Geostatistical Inversion Technology in Nanpu Oilfield: taking 1-5 area in the Dongyi section of Nanpu Depression as an example

Small faults are developed in Nanpu 1-5 areas of Nanpu Oilfield. Due to the influence of seismic data resolution, it is difficult to predict the spatial distribution of thin reservoirs. In addition, the structure of reservoir sand bodies is unclear. In this paper, firstly, based on seismic, logging, and production dynamic data from the work area, theoretical analysis is conducted on sequence stratigraphy, sedimentary petrology, seismic sedimentology, and development geology. On this basis, an accurate reservoir geological model is established based on geostatistical inversion technology. Finally, geological model well dilution inspection, production dynamic data inspection, and production application analysis are carried out. Research results show that: the geological model has a compliance rate of over 90% for well dilution and dynamic verification. The planar distribution characteristics of high-quality reservoirs in Nanpu 1-5 areas are accurately predicted, showing an overall high in the middle and low on the east and west sides. In response to the remaining oil enrichment areas, additional drilling and water injection measures have been deployed, forming a plan to improve the recovery rate in Nanpu 1-5 areas.

Utilizing well-reservoir pseudo-connections for multi-stage hydraulic fracturing modeling in tight gas saturated formations

Purpose. Research is aimed at integrating multi-stage hydraulic fracturing in horizontal wells with hydrodynamic simulation as a mandatory part of planning the mining of any shale oil or gas reservoir. Methods. Geological and hydrodynamic reservoir modeling is part of the research. The properties and geometries of the hydraulic fracture network and its representation in the dynamic reservoir model were assessed. The comparative characterization was carried out based on the two methods of fracture modeling: cell dimension reduction for explicit fracture modeling (LGR – local grid refinement) and implicit fracture modeling method, presented in this paper, with additional pseudo-connections between well and reservoir. Findings. A hydrodynamic model for low-permeable reservoir, produced by horizontal well, hydraulically fractured with 5 stages, has been generated. This model is calibrated to the production history and flowing bottom hole pressure by applying two methods of fracture modeling. Modeling results show that it is possible to replicate historical well production by using both methods. However, the proposed method with pseudo connections has several advantages compared to the generally accepted, local grid refinement (LGR) method. Originality. For the first time, a system of pseudo connections between well and reservoir was constructed to model a multi-stage hydraulic fracturing for a hydrodynamic model of tight reservoir. Hydrodynamic simulation results were refined and calibrated to the history of hydrocarbon production and flowing bottom hole pressure data using the pseudo-connections and LGR methods. The similarity of the results by applying LGR and pseudo-connections methods was revealed. Practical implications. The use of pseudo connections for hydraulic fracturing modeling can reduce simulation run time for cases where multi-stage hydraulic fracturing has already been carried out or is planned in the future. Additionally, the use of this method allows testing a larger number of realizations and scenarios, including hydraulic fracturing design (number of stages, size and conductivity of resulted fracture systems, fracture orientation, etc.), well placement and fracture growth relative to well trajectory. Also, there is no need to rebuild a model every time for each realization, as is the case with the LGR method.

Method for predicting the injection pressure for horizontal wells in fractured tight sandstone reservoirs

Hydraulic fracturing and horizontal well drilling are the key technologies for increasing the production of continental tight sandstone reservoirs. Taking the typical fractured tight sandstone in the Yuan-287 block of the Ordos Basin as an example, a reservoir geologic model is established based on the stratigraphic correlation of 206 wells. The model and 3D paleostress field are combined to predict fracture parameters such as fracture density and strike. Using reservoir breakdown pressure (RBP) monitoring data and other data such as reservoir physical and mechanical parameters, tectonic fracture characteristics, and in situ stress parameters, a quantitative evaluation model of the RBP, which predicts the 3D distribution of RBP, is established via stepwise regression, and the factors controlling the RBP are analyzed. The rock P-wave velocity, horizontal minimum principal stress, and fracture density are found to be three key parameters that control the breakdown pressure of this tight sandstone reservoir. By comparing the fracture opening pressure of subsurface tectonic fractures with the RBP, a new method for predicting the optimal water injection pressure of this reservoir is developed. This work provides a valuable evaluation model for accelerating the efficient development of continental tight sandstone reservoirs.

Unleashing geological sequestration potential of mature oilfield by enforcing 4-dimensional seismic model-based inversion in Widuri Field, Indonesia

Implementing reservoir characterization by undertaking seismic inversion on time-lapse surveys is very effective for observing the distribution and changes in the hydrocarbon reservoir. In mature oilfields, these changes are most likely influenced by the thermodynamic activities including the injection of fluid into the reservoir, which can change the volume, pressure, and composition of the geological formations. Fluid injection (in this case, water injection) into the reservoir is typically used as an oil and gas booster to increase production through EOR (Enhanced Oil Recovery). However, in light of CCUS (Carbon Capture Utilization and Storage) application, injecting CO2 can be considered as a new EOR strategy development, with the dual objectives of increasing oil and gas production as well as lowering carbon emissions at the same time. The 4-dimensional (4D) seismic data available over Widuri Field covers an area of 125 km2, with 884 inlines and 905 crosslines, acquired in 1991 and 2004 over the same area. The inversion algorithm is using seismic deconvolution to generate an acoustic impedance model before developing a geological reservoir model. Reservoir characterization was conducted in this study to obtain detailed information of the reservoir zones by determining the impact of water injection that replaces hydrocarbons. Intervals and areas with an abundance of water can be considered as potential CO2 sequestration in the future, as a part of the CCUS application. In conclusion, the findings of increasing impedance from inversion data from 1991 to 2004 can indicate the presence of existing porosity and permeability. This evidence could indicate reservoir capability as CO2 storage.

Integrated Optimization of Hybrid Steam-Solvent Injection in Post-CHOPS Reservoirs with Consideration of Wormhole Networks and Foamy Oil Behavior

Summary For this paper, integrated techniques have been developed to optimize the performance of the hybrid steam-solvent injection processes in a depleted post-cold heavy oil production with sand (CHOPS) reservoir with consideration of wormhole networks and foamy oil behavior. After a reservoir geological model has been built and calibrated with the measured production profiles, its wormhole network is inversely determined using the newly developed pressure-gradient-based (PGB) sand failure criterion. Such a calibrated reservoir geological model is then used to maximize the net present value (NPV) of a hybrid steam-solvent injection process by selecting injection time, soaking time, production time, injection rate, steam temperature, and steam quality as the controlling variables. The genetic algorithm (GA) has been integrated with orthogonal array (OA) and Tabu search to maximize the NPV by delaying the displacement front as well as extending the reservoir life under various strategies. Considering the wormhole network and foamy oil behavior and using the NPV as the objective function, such a modified algorithm can be used to allocate and optimize the production-injection strategies of each huff ‘n’ puff (HnP) cycle in a post-CHOPS reservoir with altered porosity and increased permeability within a unified, consistent, and efficient framework.

Stochastic reconstruction of geological reservoir models based on a concurrent multi-stage U-Net generative adversarial network

For complex geological reservoir modeling, some numerical-simulation-based methods, such as traditional multiple-point statistics (MPS), cannot extract nonstationary patterns of training images (TIs) effectively. CPU-intensive calculations require that variables information only be stored in RAM instead of other storage mediums to avoid huge time consumption if many simulations are performed successively. Generative Adversarial Network (GAN) modeling methods are able to overcome these issues, but when the training datasets are limited, mode collapse easily occurs. Meanwhile, fixed receptive fields might cause the problem that the corresponding reconstruction cannot take local features and global features of the TIs into account simultaneously. Therefore, we propose the Concurrent Multi-Stage U-Net GAN (Con-MSUGAN) based on a single TI. The pyramid structure is used for spatial pattern multi-scale representation in Con-MSUGAN, which can capture the corresponding feature information of TIs under different scales. Meanwhile, concurrent training patterns can make network parameters in adjacent stages correlated with each other to accelerate network convergence speed, thereby realizing stochastic multi-scale reconstructions. Stationary channel and nonstationary delta facies TIs were used to verify the performance of Con-MSUGAN. Results show that simulation of different datasets using this method are more similar in terms of spatial variance, connectivity degree and facies type frequency distribution to the original TIs. Meanwhile, muti-dimensional-scaling (MDS) plots show small discrepancies between simulation results and the corresponding TI. It indicates that Con-MSUGAN can overcome the problem that complex spatial patterns are hard to reproduce. In addition, saved network parameters can be reused. A variety of equiprobability simulation results can be obtained rapidly, thereby realizing stochastic reconstruction of geological reservoir models.

Automatic reconstruction of geological reservoir models based on conditioning data constraints and BicycleGAN

For geological reservoir units with different sizes of pore spaces and relatively stronger anisotropic heterogeneities, Generative-Adversarial-Network-based (GAN) modeling methods can overcome limitation of numerical-simulation-based ones and support finely representation of nonstationary models. However, due to conditioning data weak constraints, GANs might ignore local detail features, with artifacts and noise during simulation. Some pre-processing strategies are strictly limited by the conditioning data distribution patterns, and corresponding processes should be updated frequently when new data are introduced, with relatively complicated operation. Therefore, the BicycleGAN framework was introduced in this paper. Based on bijective consistency between the latent vector and output, an image-to-image translation task with different dimensions is established, and multiple networks were coupled to realize finely representation of spatial attributes. Specifically, the mapping between conditioning data and output is established through the U-Net architecture, which not only local detail information is considered, but also reduce the impact of conditioning data distribution patterns. Meanwhile, the mapping between latent and actual test time distribution is also established by an encoding function to ensure simulation authenticities. In addition, a joint loss function combined with conditioning loss and prior loss is defined to ensure reconstruction accuracy of different facies types. Four kinds of categorical and continuous training images were selected to verify the network simulation performances. Results show that reconstruction accuracy for facies types of conditioning data is almost consistent with those of the references, keeping similarities in terms of spatial variability, connectivity, structural similarity, and facies type reproductions. Meanwhile, for the saved BicycleGAN, inputting different kinds of conditioning data once only, and a variety of simulations can be obtained rapidly, thereby realizing conditioning reconstruction of geological reservoir models.

Fracture-vuggy carbonate reservoir characterization based on multiple geological information fusion

The complexity and strong heterogeneity of carbonate reservoirs with fracture-vuggy structures present significant challenges in reservoir characterization. To address these challenges, we propose a novel multi-element information fusion modeling approach. This approach is designed to integrate multiple methods and incorporate multi-probability fusion at various facies and scales, thereby bridging the gap between geological information and reservoir modeling. Our methodology involves four key steps. First, the statistics between frequency of karst and geological information are acquired, and we quantify the statistics to regression equations. Second, these regression equations are transferred to probability bodies. The probability bodies can be applied in modeling as a soft control. But just one single body can be input in modeling process. Third, multiple probability bodies are fused into a fusion probability body by a probability fusion algorithm, which can keep the potential information of probability bodies. Finally, we apply the probability body in modeling workflow. By this way, the fusion method bridges the gap between geological information and modeling. The model established through our proposed method showed a significant level of consistency with reservoir re-evaluation, achieving an impressive 90% degree of alignment. Furthermore, the history match analysis revealed a high correlation, indicating the model's reliability. The method effectively integrates various scales and types of geological information, offering an accurate approach to complex carbonate reservoir modeling.

Contribution of ChatGPT and Other Generative Artificial Intelligence (AI) in Renewable and Sustainable Energy

In the dynamic field of renewable and sustainable energy, Artificial Intelligence (AI) integration has emerged as a crucial catalyst for enhancing efficiency, cost reduction, and addressing multifaceted challenges. This work delves into the performance and contributions of ChatGPT, a prominent representative of large AI language models, within the context of renewable and sustainable energy. The research endeavors to explore ChatGPT's efficacy and role across a diverse spectrum of renewable energy aspects, spanning solar energy, wind energy, biomass energy, hydropower, geothermal energy, energy storage, grid integration, energy efficiency, materials science, policy, economics, environmental impact, energy accessibility, and advanced biofuels. The investigation commences with solar energy, where ChatGPT showcases impressive capabilities in data analysis, modeling, and forecasting. It facilitates solar panel placement optimization, energy production prediction, and overall efficiency enhancement. Likewise, in the realm of wind energy, ChatGPT proves invaluable for tasks such as wind turbine control, maintenance scheduling, and wind speed prediction. In biomass energy, ChatGPT aids in feedstock selection, process optimization, and emissions reduction. In the hydropower sector, it supports reservoir management and river flow prediction, thereby optimizing energy output. Geothermal energy benefits from ChatGPT's geological analysis, reservoir modeling, and exploration strategies. Energy storage solutions are indispensable for grid stability, and ChatGPT contributes to the advancement of cutting-edge battery technologies, augmenting energy storage capacity and lifespan. Furthermore, ChatGPT's insights foster the evolution of smart grids, ensuring efficient energy distribution and effective demand management. Additionally, ChatGPT provides invaluable insights into policy and economics, offering recommendations for incentivizing the adoption of renewable energy sources while considering environmental impact and sustainability. It also contributes to the advancement of tidal and wave energy technologies, as well as the development of advanced biofuels. The outcomes of this research paper underscore the potential of AI and ChatGPT in shaping the future of renewable energy, expediting progress toward a sustainable energy ecosystem.

Finite analytical method on corner‐point grid for fluid flow in heterogeneous porous media

AbstractThe three‐dimensional (3D) corner‐point grid system, as an industrial standard, has been widely used in oil reservoir geological modeling and numerical simulation due to its versatility compared to traditional orthogonal grids. The finite analytical method (FAM) is proposed for corner‐point grid systems in this article, which can greatly improve the simulation accuracy, especially for strongly heterogeneous porous media. Based on the approximate analytical solution around the edge of the corner‐point cells, the internodal transmissibility of two adjacent cells is recalculated to replace the traditional one. The traditional internodal transmissibility is calculated based on the harmonic mean of the permeabilities of the two adjacent cells, which will greatly underestimate the transmissibility and lead to an uncontrollable error as the strength of heterogeneity increases. The proposed FAM can calculate the internodal transmissibility rather accurately, and its accuracy is irrelevant to the strength of the heterogeneity, which is the main advantage of FAM. Numerical tests show that the simulation results of the proposed FAM converge much faster than the traditional method as the cells are refined. The proposed FAM can be easily extended to the simulation of multiphase flow and be easily embedded in commercial reservoir numerical simulation software.

Optimizing scenarios of a deep geothermal aquifer storage in the southern Upper Rhine Graben

Based on a newly developed geological 3D reservoir model for the demonstration site of the ‘Freiburger Bucht’ in the Upper Rhine Graben (SW Germany), geothermal development and realization concepts of an aquifer thermal energy storage (ATES) in the Buntsandstein aquifer were elaborated and energetically evaluated by numerical modeling. The thermal–hydraulic coupled modeling was performed with the FE-software OpenGeoSys and COMSOL. For this purpose, the geological model was converted into a numerical model and calibrated by local and regional, hydrogeological and geothermal measured values. A detailed study based on two-phase storage-heating cycles per year with constant injection temperature on the ‘hot side’ of the ATES, different volumetric flow rates, and temperature spreads was performed to quantify possible storage capacities, energies, and efficiencies. The calculated efficiency of the cyclic storage operation in this study, averaged over 10 storage heating cycles, are between 50 and 85%, depending on flow rate and temperature spread. The efficiency of the individual storage heating cycles increases from year to year in all scenarios considered, as the ‘hot side’ of the storage heats up in the long term. To increase ATES’ efficiency, also horizontal wells were integrated into the numerical model and the results were compared with those of inclined wells.

Heat Production Capacity Simulation and Parameter Sensitivity Analysis in the Process of Thermal Reservoir Development

The development of a geothermal system involves changes in the temperature field (T), seepage field (H), stress field (M), and chemical field (C) and the influence among them and injecting the heat extraction working fluid into the injection well that flows (migrating) through natural fractures and exchanges heat with the geothermal high-temperature rock. At the same time, the injection of low-temperature working fluid will induce thermal stress, resulting in changes in the reservoir temperature field and stress field. To study the influence factors and influence degree of heat production performance and mining life under multi-field coupling in the process of thermal reservoir development, based on THMC multi-field coupling numerical simulation software, this paper deeply studies the control differential equations and boundary coupling conditions of rock mass (fracture) deformation, seepage, heat exchange, the chemical reaction, and other processes based on the numerical solution method of the discrete fracture network model, simulating heat production capacity during the deep geothermal resource extraction process. The reservoir geological model analysis and generalization, parameter setting, boundary conditions, initial condition settings, mesh generation, and other steps were carried out in turn. Two different heat extraction working fluids, water, and CO2 were selected for numerical simulation in the mining process. The changes in the thermal reservoir temperature, net heat extraction rate, and SiO2 concentration during the thirty years of systematic mining were compared. The results show that CO2 has a better heat extraction effect. Finally, the reservoir thermal conductivity, heat capacity, well spacing, injection temperature, fracture spacing, fracture permeability, fracture number, fracture length, and other parameters were set, respectively. The parameter variation range was set, and the parameter sensitivity analysis was carried out. The numerical simulation results show that the engineering production conditions (injection temperature, well spacing) have little effect on the thermal efficiency and mining life, and the properties of fractures (fracture permeability, fracture number, fracture length) have a great influence.

Influence of key geological factors on fluid production behaviors in marine natural gas hydrate reservoirs: A case study

Accurate geological model of hydrate reservoir is the prerequisite of obtaining the credible prediction results. Not only stress sensitivity and anisotropy of permeability but also non-uniformity in hydrate saturation and permeability distribution are key geological factors influencing fluid production behaviors. However, they have been overlooked to some extent in previous numerical simulations. To highlight the significance of these factors, this study develops a robust production model at site AT1 based on geological data and laboratory tests. Then we systematically investigate the effects of the aforementioned factors on production performance. The simulation results exhibit that all the factors have notable impacts on fluid production behaviors, especially the non-uniform hydrate saturation and permeability distributions. Ignoring the permeability stress sensitivity and adopting the homogeneous simplification of hydrate saturation may overestimate gas and water production. Besides, various characterization methods of reservoir permeability can give rise to the significantly different production behaviors for heterogeneous hydrate reservoirs. The stronger the reservoir permeability anisotropy, the better the production performance. In order to achieve the reliable predictions, the geological model built should properly incorporate these factors during numerical modeling. These findings provide valuable guidance for constructing robust models and optimizing production strategies for natural gas hydrate reservoirs.

Optimization Study of Injection and Production Parameters for Shallow- and Thin-Layer Heavy Oil Reservoirs with Nitrogen Foam-Assisted Steam Flooding

Shallow- and thin-layer heavy oil reservoirs are characterized by their shallow burial, thin thickness, high viscosity, and scattered distribution. After years of steam injection development, several issues have emerged, including a highly comprehensive water cut in the reservoir and serious steam channeling. Therefore, there is an urgent need to change the development approach to enhance crude oil recovery. It has been discovered that developing heavy oil reservoirs through nitrogen foam-assisted steam flooding can effectively address the challenges encountered in pure steam development. This paper takes H Oilfield Block A as a case study, analyzes the geological characteristics and development status of the reservoir in this block, and predicts the recovery of steam injection development in this block using the injection-production characteristic curve method. Furthermore, by establishing a reservoir geological model and fitting it to the historical behavior of the target reservoir, the nitrogen foam-assisted steam flooding injection and production parameters were optimized. The optimal parameters are as follows: optimal steam injection intensity of 2.0 t/(d·ha·m), optimal production/injection ratio of 1.2:1, optimal nitrogen foam slug injection volume of 0.15 PV, optimal nitrogen/steam ratio of 2:1, and intermittent injection between 3 and 4 foam slugs. It is anticipated that this optimized scheme will result in a predicted increase in final recovery of 13.55%. The findings of this study hold significant importance in guiding the application of nitrogen foam-assisted steam flooding in shallow and thin heavy oil reservoirs.

Fracture Modeling of Deep Tight Sandstone Fault-Fracture Reservoir Based on Geological Model and Seismic Attributes: A Case Study on Xu 2 Member in Western Sichuan Depression, Sichuan Basin

With significant geological reserves and high resource abundance, the Xujiahe Formation in the Western Sichuan Depression is considered a key target for natural gas exploration and development in continental clastic rocks within the Sichuan Basin. However, this formation remains underdeveloped. Critical to forming “sweet spots” of tight reservoir is the presence of fractures. Based on available data sources, including core samples, well logs, and outcrop data, we utilized a combination of geophysical and geological modeling techniques to clarify the characteristics of effective fractures in tight gas reservoirs. This allowed us to construct a geological model of a tight sandstone fault-fracture gas reservoir in the Xu 2 Member of the Xujiahe Formation located in the Xinchang area, which represents a fault-fracture reservoir formed by high-angle faulting-derived fractures and controlled by the S-N trending fault. With this model, a variety of seismic attributes, including likelihood and entropy, was used to predict the fault-fracture reservoir. Furthermore, geological information, well logs, and seismic attributes were integrated for characterizing the fractures of different scales. The cutoff on various attributes for characterizing the fault-fracture reservoir was defined, and the distribution of the fault-fracture reservoir was delineated. By using the geological modeling technique, the fracture model of the fault-fracture reservoir comprising natural fractures at different scales was built. This model provides further guidance for the exploration and development of the Xu 2 Member tight gas reservoirs in the Xinchang area and, as demonstrated by drilling results, has achieved remarkable effects in practice. This approach has shown good performance in characterizing fracture models. However, due to the complexity of fractures and the discrepancy between the scale of fractures and the scale that can be predicted by geophysical methods, there may still be some uncertainties associated with this method.

Geophysical Modeling and Its Contribution on the Reservoir Characterization of Al Baraka in El Gallaba Plain, South Egypt

Summary The early Cretaceous formations in recent years are considered significant potential hydrocarbon-bearing rocks in many rift basins such as Komombo, south Egypt. Therefore, this study is focused on the critical analysis and interpretation of well logging together with seismic reflection data on the Al Baraka petroliferous reservoir in the Komombo subbasin. The interpretation of these data was used to construct the first 3D geophysical models in this area which were subsequently interpreted in terms of their potential to be hydrocarbon-bearing or not. The 3D petrophysical models were deduced to illustrate the spatial distribution and propagation of the petrophysical properties (laterally and vertically) within the reservoir. Additionally, 3D seismic models were prepared to get a comprehensive, in-depth picture of how the productive hydrocarbon reservoir zones are structurally controlled in different depths. So, these models are crucial for explaining reservoir characteristics and providing supported geological reservoir models for precise reservoir performance prediction. This study aims to differentiate and determine hydrocarbon potential zones in terms of the petroleum system. The results of these progressive analyses showed that only two zones (C and D) in the Six Hills Formation are considered the most productive zones because they have a large thickness of sand bodies, low-water saturation values, high porosity, and high permeability. These zones are located in the northeastern and central parts of the studied area, which represent the depocenter of the subbasin. This evidence supported and confirmed the presence of petroleum accumulations in certain zones within the Six Hills Formation. Therefore, this work can give and encourage experts with adequate knowledge to understand the development of the rift basins in Komombo and other basins in middle and south Egypt.

Buoyant Flow of H2 Vs. CO2 in Storage Aquifers: Implications to Geological Screening

Summary Hydrogen will play an important role in the quest to decarbonize the world’s economy by substituting fossil fuels. In addition to the development of hydrogen generation technologies, the energy industry will need to increase hydrogen storage capacity to facilitate the development of a robust hydrogen economy. The required hydrogen storage capacity will be much larger than current hydrogen and natural gas storage capacities. There are several geological storage options for hydrogen that include depleted hydrocarbon fields and aquifers, where more research is needed until the feasibility of storing hydrogen at scale is proved. Here, we investigate the buoyant flow of H2 (as a working gas) vs. CO2 (as a cushion gas) separately in a representative storage aquifer. Buoyant flow can affect the maximum storage, capillary trapping, likelihood of leakage, and deliverability of aquifer-stored hydrogen. After building a 2D geological reservoir model initially filled with saline water, we ran numerical simulations to determine how hydrogen placed at the bottom of an aquifer might rise through the water column. The Leverett j-function is used to generate heterogeneous capillary entry pressure fields that correlate with porosity and permeability fields. Hydrogen viscosities were based on the Jossi et al. correlation, and the density was modeled using the Peng-Robinson equation of state. We then simulated several scenarios to assess flow during short- (annually) and long- (several years) term storage. For comparison purposes, we also ran CO2 storage simulations using the same geological model but with CO2-brine-rock properties collected from the literature. For a representative storage aquifer (323 K, 15.7 MPa, and mean permeability of 200 md), significant fingering occurred as the hydrogen rose through the saline water column. The hydrogen experienced more buoyant flow and created flow paths with increased fingering when compared with CO2. Individual hydrogen fingers are thinner than the CO2 fingers in the simulations, and the tips of hydrogen finger fronts propagated upward roughly twice as fast as the CO2 front for a typical set of heterogeneity indicators (Dykstra-Parson’s coefficient Vdp = 0.80, and dimensionless autocorrelation length λDx = 2). The implications of buoyant flow for hydrogen in saline aquifers include an increased threat of leakage, more residual trapping of hydrogen, and, therefore, the need to focus more on the heterogeneity and lateral correlation behavior of the repository. If hydrogen penetrates the caprock of an aquifer, it will leak faster than CO2 and generate more vertical flow pathways. We identify possible depositional environments for clastic aquifers that would offer suitable characteristics for storage.

Reconstructing a Three-Dimensional Geological Model from Two-Dimensional Depositional Sections in a Tide-Dominated Estuarine Reservoir: A Case Study of Oil Sands Reservoir in Mackay River, Canada

A tide-dominated estuarine reservoir is an important oil reservoir. However, due to the force of bidirectional water flow, its internal structure is complex, and the heterogeneity is serious. Accurately establishing the tide-dominated estuarine reservoir model is a great challenge. This paper takes the Mackay River oil sands reservoir in Canada as the research object to establish the elaborate geological model of a tide-dominated estuarine reservoir. Through the meticulous depiction of core data, 14 kinds of lithofacies and nine kinds of architectural elements are identified, and the lithological and electrical response in sedimentary architectural elements is established. On this basis, the plane and vertical distribution of architectural elements, as well as the spatial superimposition patterns, are depicted and characterized through well seismic combination and plane and section interaction, and the representative plane and section architecture maps are obtained as 2D training images (TIs) for multi-point statistical modeling. The 2D TI is scanned by 2D data template to obtain the multi-point statistical probability of the 2D spatial architectural pattern. Then, the 2D multi-point probability is fused to generate three-dimensional (3D) multi-point statistical probability by the probabilistic fusion. Finally, Monte Carlo sampling is used to predict the spatial distribution of architectures, and an elaborate geological model of a tide-dominated estuarine reservoir is established. Compared with the traditional sequential indication modeling method, the point-to-point error of the model section based on the 2D section reconstruction method is only 25.92%, while the sequential indication modeling method is as high as 58.52%. Even far from the TI, the point-to-point error of the 2D section model is 33.13%. From the cross-validation, the average error of the 2D section is 11%, while the sequential indicator modeling error is 23.1%, which indicates that the accuracy of 2D reconstruction of the estuarine reservoir model is high, and this method is suitable for the establishment of the tide-dominated estuarine reservoir model.