Accurately characterizing fracture network morphology is necessary for flow simulation and fracturing evaluation. The complex natural fractures and reservoir heterogeneity in unconventional reservoirs make the induced fracture network resulting from hydraulic fracturing more difficult to describe. Existing fracture propagation simulation and fracture network inversion methods cannot accurately match actual fracture network morphology. Considering the lightning breakdown similar as fracture propagation, a new efficient approach for inversion of fracture network morphology is proposed. Based on the dielectric breakdown model (DBM) for lightning breakdown simulation and similarity principle, an induced fracture propagation algorithm integrating reservoir in-situ stress, rock mechanical parameters, and stress shadow effect is proposed. The fractal index and random function are coupled to quantitatively characterize the probability distribution of induced fracture propagation path. At the same time, a matching rate function is proposed to quantitatively evaluate the fitting between fracture network morphology and the micro seismic data. Combined with automatic history matching method, the actual fracture network morphology can be inverted with the matching rate as objective function. The proposed approach is applied to fracture network simulation of mult-fractured horizontal wells of shale oil reservoir in China, and the fracture networks from inversion fit well with the micro seismic data. A simulation of 94 fractures in the 32 section of Well X2 shows that the well propagates more obvious branch fractures. The single-wing fracture network communicates approximately 200m horizontally and approximately 10m vertically. In single fracture flow simulation, it is necessary to consider the influence of complex fracture network morphology, but when simulating fluid flow for a single well or even a reservoir, only the main fracture needs to be considered. This paper proposes an induced fracture propagation algorithm that integrates reservoir in-situ stress, rock mechanical parameters, and stress shadowing effects. This algorithm greatly improves the calculation efficiency on the premise of ensuring the accuracy of induced fracture network morphology. The approach in this paper provides a theoretical basis for flow simulation of stimulated reservoirs and optimization of fracture networks.
Multistage stimulation horizontal wells are prerequisite technologies for efficient development of unconventional reservoir. However, the induced fracture network morphology from hydraulic fracturing is very complex and affected by many factors, such as the in situ stress, rock mechanical properties, and natural fracture distribution. The large numbers of natural fractures and strong reservoir heterogeneity in unconventional reservoirs result in enhanced complexity of induced fractures from hydraulic fracturing. Accurate description of fracture network morphology and the flow capacity in different fractures form an important basis for production forecasting, evaluation (or optimization) of stimulation design, and development plan optimization. This paper focuses on hydraulic fracturing in unconventional reservoirs and discusses the current research advances from four aspects: (1) the prediction of induced fracture propagation, (2) the simulation of fluid flow in complex fracture networks, (3) the inversion of fracture parameter (fracture porosity, fracture permeability, etc.), and (4) the optimization of hydraulic fracturing in unconventional reservoirs. In addition, this paper provides comparative analysis of the characteristics and shortcomings of the current research by outlining the key technical problems in the study of flow characterization, parameter inversion, and optimization methods for stimulation in unconventional reservoirs. This work can provide a certain guiding role for further research.
After steam discharge in heavy oil reservoirs, the distribution of temperature, pressure, and permeability in different wells becomes irregular. Flow channels can easily be produced, which affect the sweep efficiency of the oil displacement. Previous studies have shown that the salting-out plugging method can effectively block these channels in high-temperature reservoirs, improve the suction profile, and increase oil production. In the present study, the optimal dosage of the plugging agent is determined taking into account connection transmissibility and interwell volumes. Together with the connectivity model, a water flooding simulation model is introduced. Moreover, a non-gradient stochastic disturbance algorithm is used to obtain the optimal plugging agent dosage, which provides the basis for the high-temperature salting-out plugging agent adjustment in the field.
IntroductionNewcastle disease virus (NDV) is an important avian pathogen prevalent worldwide; it has an extensive host range and seriously harms the poultry industry. Velogenic NDV strains exhibit high pathogenicity and mortality in chickens. Circular RNAs (circRNAs) are among the most abundant and conserved eukaryotic transcripts. They are part of the innate immunity and antiviral response. However, the relationship between circRNAs and NDV infection is unclear.MethodsIn this study, we used circRNA transcriptome sequencing to analyze the differences in circRNA expression profiles post velogenic NDV infection in chicken embryo fibroblasts (CEFs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to reveal significant enrichment of differentially expressed (DE) circRNAs. The circRNA- miRNA-mRNA interaction networks were further predicted. Moreover, circ-EZH2 was selected to determine its effect on NDV infection in CEFs.ResultsNDV infection altered circRNA expression profiles in CEFs, and 86 significantly DE circRNAs were identified. GO and KEGG enrichment analyses revealed significant enrichment of DE circRNAs for metabolism-related pathways, such as lysine degradation, glutaminergic synapse, and alanine, aspartic-acid, and glutamic-acid metabolism. The circRNA- miRNA-mRNA interaction networks further demonstrated that CEFs might combat NDV infection by regulating metabolism through circRNA-targeted mRNAs and miRNAs. Furthermore, we verified that circ-EZH2 overexpression and knockdown inhibited and promoted NDV replication, respectively, indicating that circRNAs are involved in NDV replication.ConclusionsThese results demonstrate that CEFs exert antiviral responses by forming circRNAs, offering new insights into the mechanisms underlying NDV-host interactions.
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