Petroleum Research最新文献

The reservoir heterogeneity of Suizhong 36-1 oilfield is very obvious, the average permeability reaches 2000mD. Long-term water injection development leads to serious water channeling in high permeability layers, resulting in ineffective circulation of injected water and reduction of oil recovery. It is urgent to form an effective EOR method. In this paper, the oil displacement effect of different combination slugs including polymer gel, polymer microsphere and surfactant is evaluated by means of conformance control and chemical flooding. Three-layer heterogeneous 3-D plate model is used for oil displacement experiment. The experimental results show that the combination slug sequentially composed of polymer gel, polymer microspheres and surfactant have the best oil displacement effect with the oil recovery increment by 21.2% after the first water flooding. In addition, using the best slug combination for two rounds flooding, the recovery factor increased by 28.2% compared with the first water flooding. This paper provides some new insights for enhanced oil recovery in strong heterogeneity reservoir.

This paper focuses on determining total organic carbon (TOC) from boreholes in the Kalahari Basin, Botswana, using Passey's method. The Kalahari Karoo basin is one of several basins in southern Africa filled with Late Carboniferous to Jurassic sedimentary strata that host Permian age coal seams. Nine exploration boreholes (wells) drilled in the central Kalahari Karoo basin are used to determine the Total Organic Carbon potential. Vitrinite reflectance (R_o), proximate and ultimate analyses were conducted on cored coal intervals. Passey's ΔLogR method applied in this study employs resistivity and porosity logs to identify and quantify potential source rocks. Results of Passey's method compared with laboratory-measured carbon showed that Passey's method effectively identifies coal intervals. In terms of TOC calculations, the method works poorly in coal metamorphosed by dolerite intrusions. The heat affected coal samples had R_o from 0.77% to 5.53% and increased in maturity from primarily maceral controlled to high volatile bituminous and anthracite coal. Results from proximate analysis showed compositional changes in the coal were controlled by proximity to sill intrusion, with a decrease in Fixed Carbon and an increase in ash yield in the contact metamorphism zone (2–12 m from sill). For the unaltered coal that has undergone burial maturation displaying R_o of 0.44%–0.65%, the method works well. In unintruded boreholes, correlations between Carbon and calculated TOC indicate strong relationships. Passey's ΔLogR method proved to be a suitable method of estimating TOC on coal that has undergone burial maturation. This study has demonstrated that TOC calculated from the sonic log is more reliable in coal not affected by contact metamorphism than TOC calculated from the density log.

Hydraulic fracturing (HF) is an effective way to intensify oil production, which is currently widely used in various conditions, including complex carbonate reservoirs. In the conditions of the field under consideration, the hydraulic fracturing leads to a significant differentiation of technological efficiency indicators, which makes it expedient to study the patterns of crack formation in detail. Studies were carried out for all wells, which were considered as the objects of impact, to assess the spatial orientation of the cracks formed. The developed indirect method was used for this purpose, the reliability of which was confirmed by geophysical methods. During the analysis, it was found that in all cases, the crack is oriented in the direction of the section of the development system element characterized by the maximum reservoir pressure. At the same time, the reservoir pressure values for all wells were determined at one point in time (at the beginning of HF) using machine learning methods. The reliability of the machine learning methods used is confirmed by the high convergence with the actual (historical) reservoir pressures obtained during hydrodynamic studies of wells. The obtained conclusion about the influence of the reservoir pressure on the patterns of fracture formation should be taken into account when planning hydraulic fracturing under the conditions studied.

In the last few years, the use of artificial intelligence (AI) and machine learning (ML) techniques have received considerable notice as trending technologies in the petroleum industry. The utilization of new tools and modern technologies creates huge volumes of structured and un-structured data. Organizing and processing of these information at faster pace for the performance assessment and forecasting for field development and management is continuously growing as an important field of investigation. Various difficulties which were faced in predicting the operative features by utilizing the conventional methods have directed the academia and industry toward investigations focusing on the applications of ML and data driven approaches in exploration and production operations to achieve more accurate predictions which improves decision-making processes. This research provides a review to examine the use cases and application of AI and ML techniques in petroleum industry for optimization of the upstream processes such as reservoir studies, drilling and production engineering. The challenges related to routine approaches for prognosis of operative parameters have been evaluated and the use cases of performance optimizations through employing data-driven approaches resulted in enhancement of decision-making workflows have been presented. Moreover, possible scenarios of the way that artificial intelligence will develop and influence the oil and gas industry and how it may change it in the future was discussed.

Although significant amount of H₂S (sour gas) rich natural gas is estimated globally, but not much attention has been given to the application of H₂S in the oil recovery process. Recent studies on the use of H₂S in oil recovery processes showed that H₂S has the potential of improving the oil recovery, and it can be even more effective than using CO₂ in some processes. H₂S can equally dissolve in the water, react with the reservoir rock to change its surface charge, porosity, and permeability. However, previous investigations on H₂S oil recovery attributed the improved oil recoveries to the higher miscibility of H₂S in the oil, and the reduction in the oil viscosity. Therefore, there is limited understanding on the H₂S-oil-brine-rock geochemical interactions, and how they impact the oil recovery process. This study aims to investigate the interactions between H₂S, oil, and carbonate formations, and to assess how the combination of H₂S and low salinity water can impact the wettability and porosity of the reservoirs. A triple layer surface complexation model was used to understand the influence of key parameters (e.g., pressure, brine salinity, and composition) on the H₂S-brine-oil-rock interactions. Moreover, the effects of mineral content of the carbonate rock on H₂S interactions were studied. Thereafter, the results of the H₂S-oil-brine-rock interactions were compared with a study where CO₂ was used as the injected gas. Results of the study showed that the seawater and its diluted forms yielded identical ζ-potential values of about 3.31 mV at a pH of 3.24. This indicates that at very low pH condition, pH controls the ζ-potential of the oil-brine interface regardless of the brine's ionic strength. The study further demonstrated that the presence of other minerals in the carbonate rock greatly reduced the calcite dissolution. For instance, the calcite dissolution was reduced by 4.5% when anhydrite mineral was present in the carbonate rock. Findings from the simulation also indicated that CO₂ produced negative ζ-potential values for the carbonate rocks, and these values were reduced by 18.4%–20% when H₂S was used as the gas phase. This implies that the H₂S shifted the carbonate rock ζ-potentials towards positive. The outcomes of this study can be applied when designing CO₂ flooding and CO₂ storage where the gas stream contains H₂S gas since H₂S greatly influences the dissolution of the carbonate mineral.

The main objective of this paper is to construct a static model that compress the uncertainties of the stochastic distribution of the reservoir properties of the Bahariya Formation in Heba field, at the northeastern portion of the Western Desert. This model has been constructed through the integration of the interpretations of the eighteen 2D seismic sections and the analysis of well logs data for four wells (HEBA 300X, E.BAH-E−1X, E.BAH-D-1X, and HEBA 10X) drilled in the study area. This set of data was implemented in a harmonic workflow. Structural framework was the first step created on the basis of the seismic and well log interpretations. Model zonation was mainly managed by the marine flooding events took place during the Cenomanian period. The trapping faults position uncertainty has been compressed through the tying of the seismic profiles with the identified fault cuts in the well data. Effective porosity spectrum was broke up into three reservoir qualities. The results showed heterogeneous facies qualities for oil production in specific five zones in the topmost part of the Bahariya Formation. The effective porosity model was generated stochastically considering the normal distribution for each reservoir quality. Water saturation was distributed by two methods; 1) Sequential Gaussian Simulation that was co-simulated by porosity model. 2) Log-based saturation height function for each reservoir quality. This methodology provided as accurate as possible estimates for the volume calculation by quantifying the sensitivity of the important parameters such as oil contact. Additionally, the model was prepared to be used as a front end for dynamic simulation.

This research examined the use of 75 nm zinc oxide nanoparticles (nano ZnO) and polyethylene butene (PEB) to decrease the viscosity of Nigerian waxy crude oil. The rheology of the crude oil was assessed by measuring the viscosity and shear stress of samples containing PEB at 500, 1000, 2000, 3000, 4000 or 5000 ppm and nano ZnO at 1, 2, 3 or 4 wt% between 10 and 35 °C at shear rates from 1.7 to 1020 s⁻¹. Rheological modeling indicated that a power law pseudoplastic model was the best fit for the experimental data, giving a regression coefficient of 0.99. The addition of these inhibitors induced Newtonian fluid behavior in the crude samples such that the shear stress-shear rate relationship plots were linear at all temperatures. The optimum concentrations of the inhibitors in this study were 2000 ppm PEB (providing a 33% viscosity reduction) and 1 wt% nano ZnO (providing a 26% viscosity reduction). A combination of these additives at these concentrations provided a synergistic effect and gave a greater viscosity reduction of 41%. This work demonstrates that a blend of ZnO nanoparticles and PEB can improve the flowability of waxy crude.