No abstract

Low-permeability oil reservoirs generally have the low production, production rapid productivity decline, and low-ultimate recovery. Staged fracturing is usually conducted for horizontal wells. Hydraulic fracturing technology is generally used to improve fracture conductivity and well productivity, which is one of the key technologies for Enhance Oil Recovery (EOR). How to accurately characterize and simulate the distribution characteristics of hydraulic fracture network in 3D space is particularly important. The stress interference between hydraulic fractures as the objective mechanical behavior in the process of staged fracturing affects the geometry fracture network and the productivity of the reservoir post-fracturing. The hydraulic fractures simulation in natural fractured reservoirs is complex shapes, mainly because natural fractures affect the propagation path of hydraulic fractures. The theoretical model used to describe the hydraulic fracturing in homogeneous reservoirs cannot accurately show the complexity of the spatial morphology of hydraulic fractures in naturally fractured formations. CNCP (the operator) urgently need a mechanical model that can show the stress interference behavior between multiple fractures and the direction of hydraulic fracture propagation, and be used to simulate the spatial form of multiple hydraulic fractures in staged fracturing of horizontal wells and their propagation behavior in naturally fractured formations. Aiming at the impact of natural fractures in the reservoir on the propagation path of hydraulic fractures, this paper established a mechanical model for distinguishing interference behavior of natural fractures and hydraulic fractures. And analyzed the stress field at the tip of the hydraulic fracture and the stress field acting on the natural fracture surface based on the theories related to rock mechanics and fracture mechanics. On the basis of coupling the 3D geomechanical model and the 3D Discrete Fracture Network (DFN) model, this paper established the discriminant model for hydraulic fractures penetrating natural fractures in 3D space to conduct hydraulic fracture propagation simulation for the horizontal well. The research results can be used to optimize the hydraulic fracturing treatment design, and provide technical support for the effective production and profitable development of low-permeability reservoir resources.

Re-fracturing treatments of horizontal wells are increasingly gaining popularity to address the issue of rapid production decline and low recovery ratio for the conglomerate reservoir of the Mahu Oilfield. How to effectively select the horizontal wells with potentiality for re-fracturing and conduct the re-fracturing operation to achieve the purpose is the key problem that needs to be investigated urgently. However, the conventional methods for vertical wells are not in our consideration, and some methods for horizontal wells have their limits for the Mahu reservoir. To cope with problems mentioned above, fourteen factors from geology parameters, engineering parameters, and production performance parameters are considered to establish a multi-level evaluation model to quantify the potentiality of each horizontal well for re-fracturing in the Mahu Oilfield. First, the analytic hierarchy process (AHP) is used to obtain the weights of various factors affecting the productivity of horizontal wells, and on this basis, the subordination degree and evaluation matrix are then calculated, and finally, the fuzzy synthetic determination is obtained to determine the candidate wells for re-fracturing. The results have shown that the weights corresponding to engineering parameters obtained by the AHP method are the largest, followed by geology parameters, and the weights of production performance parameters are the minimal relatively; the number of fractures and the sand quantity of single cluster are the main controlling factors in engineering factors, and the initial formation pressure is the main controlling factor in geological factors; there is obvious correlation between the cumulative oil production after 90 days of primary fracturing with final cumulative production. Wells M15, M13, and M7 rank top three among the candidate wells. Through re-fracturing treatment by temporary plugging, the daily oil production of well M15 has increased significantly and is even higher than that of the primary hydraulic fracturing stimulation, confirming the reliability of the proposed selection method.

Water injection before re-stimulation has a positive effect to mitigate the “frac hit” and increase oil production in tight reservoirs. However, the study of water injection strategy optimization has not been thoroughly investigated. Some conclusions can be found in the existing literature, but the pressure and stress distribution, fractures morphology and oil production were not considered as a whole workflow during the study. In addition, the different reservoir deficit was not considered. Although technical experience and economic benefit have been obtained in some field tests, failed cases still exist. To fill this gap, a series of numerical models are established based on a tight reservoir located in northwest China. Under the different re-stimulation timing, the pressure distribution, stress distribution, and fractures morphology after water injection of different injection/production ratios are calculated, respectively. The oil and water production are predicted. The results show that, after a short period of production with a small deficit, the degree of “frac hit” is slight. Injecting water has an obvious effect on increasing oil production for both parent and infill well. After a long period of production with a large deficit, the problem of “frac hit” is very severe. Injecting water has an obvious effect on increasing oil production only for the parent well. The production of infill well is influenced by the fractures’ interference and pressure increasing comprehensively. For the well group, measured by the final cumulative oil production, the optimal injection/production ratio is different, but the water injection volume is similar, which is about 15,000 m3.