During the development of shale oil resources, fluid injection is usually involved in the process of hydraulic fracturing. Fluid injection through perforations causes near-well damage, which is closely related to the subsequent initiation and propagation of hydraulic fractures. This study is focused on the characterization of the temporal and spatial evolving patterns for near-well damage induced by fluid injection through perforations in the early stage of hydraulic fracturing. A coupled hydromechanical model is introduced in a case study in a shale oil reservoir in northwestern China. The model considers porous media flow during fluid injection. It also considers elasticity in the rock skeleton before the damage. Once the damage is initiated, a damage factor is employed to quantify the magnitude of injection-induced damage. Results show that damage evolution is highly sensitive to perforation number and injection rate in each individual perforation. Damage propagation is more favorable in the direction of the initial maximum horizontal principal stress. The propagation of damage is drastic at the beginning of fluid injection, while the damage front travels relatively slow afterward. This study provides insights into the near-well damage evolution before main fractures are initiated and can be used as a reference for the optimization of perforation parameters in the hydraulic fracturing design in this shale oil field.
To economically and efficiently develop unconventional resource plays, the industry has been spending tremendous resources to optimize completion and well spacing by piloting – a trial-and-error approach. However, the approach tends to take long time and cost significant amount of money. As the complex fracturing modeling technology advances, we question: "Can we use the latest complex fracturing modeling and reservoir simulation technologies to optimize completion and well spacing?", so that the industry can significantly save piloting time and money, and quickly find the optimal well spacing and corresponding optimal completion. A recent case study in Permian Basin has answered the question well. For a Wolfcamp well completed with crosslinked gel and wide cluster spacing in 2012, we first built a 3-D geological and geomechanical model, and a full wellbore fracturing propagation model, and then calibrated it with multi-stage fracturing pumping history; the resulting complicated fracture network model was then converted into an unstructured grid-based reservoir simulation model, which was then calibrated with the well production history. During the process, discrete natural fracture network (DFN) and stress anisotropy were systematically evaluated to study their impact on fracture growth. Microseismic and tracer log data were used to validate the hydraulic fracturing modeling results. To test if the calibrated geomechanical and reservoir models can be used to optimize well completion design, we then ran the fracturing model with the latest completion design (tighter cluster spacing, slick-water, and more fluid and proppant) and forecasted the well performance. We found out that the resulting well performance is very similar to the performance of those wells with similar completion designs in the same area. After establishing the confidence on the capacity of those models, we then further studied the impact of different completion designs on fracture dimensions and well performance. We examined the distributions of fracture length along the wellbore resulted from different cluster spacings, fracturing fluid types and volume, and proppant amount. We found out (1) the hydraulic fracture length and network complexity mainly depend on DFN and stress anisotropy, and fracturing fluid viscosity; and (2) the fracture length of those fractures initiated from different perforation clusters along wellbore is in a log-normal distribution depending on completion designs, which provides crucial insights to well interference and furthermore on well spacing. Therefore, we can reasonably model complicated fracture propagation and corresponding well performance with the latest modeling technologies, and then optimize well spacing, which should help operators save significant time and money on well completion and spacing piloting projects, and thus speed up field development decision. The paper demonstrates our novel workflow as an effective way to optimize completion design and well spacing by integrating advanced multi-stage fracture modeling with reservoir simulation in unconventional resource plays.
Flow simulation in carbonate reservoirs presents many challenges due to the frequent occurrence of vugs and natural fractures therein. In conventional reservoir simulation practices, fluid flow in vugs and fractures is usually assumed as Darcy flow, and permeability values are estimated for vuggy regions and fractures. Although such estimations are often accomplished in reasonable ways, no physical or mathematical basis exists for them, and even the assumption of Darcy flow itself is questionable. In this paper, we propose a novel workflow for the simulation of fluid flow in naturally fractured carbonate karst reservoirs. The workflow is based on simulation results of a single-phase transient Brinkman model, which provides the correct and complete description of the coupled flow in vuggy and fractured reservoirs by unifying Stokes flow in vugs and fractures with Darcy flow in the rock matrix. The new workflow proceeds through an iterative procedure by increasing the permeability values of vugs and fractures without the disadvantages of accurately estimating them, and attains the final simulation results when a convergence pattern is observed. The novel workflow is implemented and compared with the conventional approaches in commercial reservoir simulators. The workflow is first applied to single-phase flow simulations in a fine-scale 3D geological model which is generated using the multiple-point geostatistical modeling technique, and then extended to immiscible two-phase flow and other multi-phase cases. Simulation results show that in most cases our new workflow yields higher production rate predictions than conventional approaches. This is due to the fact that the permeability values of vugs and fractures estimated by conventional methods are usually lower than the permeability values required for the iterative convergence of the new workflow. The results also have further implications on the history matching process that more focus should be put on fracture geometry, i.e. fracture width and half-length, since the use of fracture permeability alone has lost its physical meaning in the novel workflow according to the Brinkman equation.
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