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Most of the oil and gas reserves in the carbonate field of interest reside in the fractured regions of the reservoir. Natural fractures are commonly observed in the reservoir. In order to support efficient workflow design, commercial software systems are providing templates of fracture description processes with utilizing discrete fracture network. To study the role of natural fractures in water influx in bottom water gas reservoirs, single-porosity, dual-porosity dual-permeability (DPDK) and embedded discrete fracture (EDFM) models were used to simulate the effect of water influx along with the fractures in fractured bottom-water-drive gas reservoirs. The saturation field and the computation time of the model of the bottom water in the matrix and the fracture were the optimized indexes of the model. The results show that under the same conditions, the EDFM model is apparently better than the former two models in simulating the phenomena of fracture water channeling, and its computation speed was increased by 48%. Based on the EDFM bottom water gas reservoir model, the influence of gas well pay-zone opening degree and gas production rate on gas reservoir development effects were analyzed under different fracture permeability and fracture density conditions. Studies have shown that when fracture permeability or fracture density increases, the gas well is more likely to show water breakthrough. When the gas well pay-zone opening degree is up to 70%, the final recovery degree is relatively higher, while the gas recovery rate is 4%, water-free production is optimal. Different fracture permeability can result in a difference of 2.4% in ultimate recovery, and the difference in water-free production is 96.6%.

This paper, based on an example from the Bereketli-Pirgui carbonate reservoir in the right bank of the Amu Darya, introduces a method for modeling the discrete fracture network (DFN) and fracture attributes with static and dynamic data. Firstly, the fracture sets, geometric attributes, and distribution of fractures are determined through a static fracture characterization (e.g., seismic-based fracture prediction, core and borehole image analysis). Then, a DFN model is built based on several geologic controls, including the structure setting, lithology, and thickness, and the hydraulic properties of fractures (aperture and conductivity) are corrected using the dynamic data (e.g., production, well test, and pressure data). Lastly, the equivalent fracture attributes model (e.g., fracture porosity and fracture permeability) is built based on the corrected DFN model. The result of the study suggests that: (1) the fracture network and the attributes model built based on geologic controls reflect the spatial distribution of fractures, and provide the attribute model for reservoir numerical simulation; and (2) the distribution of fractures in the Bereketli-Pirgui gas field controls the vertical and lateral reservoir connectivity, the difference in gas-water system, the single-well productivity, the water breakthrough time in gas well, and the DFN model has directive significance to designing the well location and optimizing the well completion method.

Field investigation and laboratory research on flysch of the Liufengguan Group in Qinling indicate the following: (1) Sandstone of the Liufengguan Group is categorized as feldspathic lithic graywacke with a minor amount of lithic graywacke in the QFR triangular diagram. Grain size ≤0.3 mm. Bedding plane structures such as groove casts and suspected flute casts can be found at the bottom of the sandstone. It is inferred that currents may have come from the southeast during deposition. Bedding structures such as ripple marks, graded bedding, parallel bedding, small-scale cross bedding, climbing bedding, suspected convolute bedding, microlamination and sliding structures have also been observed, which are of indicative significance. It is thought that the Liufengguan Group has the sedimentary characteristics of bedding, bedding plane structures and lithological assemblages of deep-sea low-density turbidity current deposits. The vertical succession of the Bouma sequence in the inner fan subfacies zone is generally incomplete: the assemblage of Ta and Tabc is commonly seen; the succession of the middle fan subfacies zone is relatively complete; and divisions Te and Tb are common in the outer fan subfacies zone. (2) The flysh of the Liufengguan Group is a sequence of deep-sea argillaceous-arenaceous submarine fan deposits, in which the authors recognize the inner, middle and outer fan subfacies and also nine types of lithofacies: normal graded sandstone (A1), medium- to thick-bedded, fine-grained sandstone (A2), medium- to thick-bedded and massive siltstone (A3), thin-bedded, fine-grained sandstone and mudstone (B1), irregular interbeds of thin-bedded, fine-grained sandstone and siltstone (B2), thin-bedded, fine-grained sandstone (C1), very thin-bedded, fine-grained sandstone (D1), olistostromes (E1) and deep-sea mudstone (F). The inner fan consists of four microfacies: natural levee (A1), water channel (A2, A3) and olistostromc (E1); in the middle fan there also occur four microfacies, i.e., branch channel (B1), branch channel (B2), interdistributary bay (D1) and olistostrome. The outer fan is made up of the branch channel (C1) and sheet sand (D1) microfacies, which alternate vertically with sediments of deep-sea plain subfacies (F). There occur fining- and thin ning-upward channel deposits in the outer-fan subfacies zone of the submarine fan of the Liufengguan Group observed in this study. The quartz content of the graywacke of the deposits is all higher than 40% and may reach as high as 60%. Therefore, on the basis of the aforementioned features, this flysh should be formed in a passive continental-margin tectonic environment.