碳酸盐岩储层压裂条件下低矿化度注水机理建模——地球化学与地质力学耦合模拟研究

Seyed Moein Hosseini, S. Kord, A. Hashemi, H. Dashti
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引用次数: 3

摘要

低矿化度水注入(LSWI)的主要问题是注入能力随时间的下降。此外,导致石油采收率增加的实际机制尚不完全清楚。在以往的研究中,未考虑地质力学效应,孔隙体积变化而体积不变,给模拟结果带来不确定性。在本文中,地球化学和地质力学模型都与流动模型相结合。对于耦合地质力学模型,在每个时间步长同时求解三个方程。然后,通过添加必要的水和矿物反应以及地层和注入水的离子浓度来耦合地球化学模型。增加注入盐水中的Ca2+浓度会导致最终采收率降低。此外,将注入盐水中的SO42−浓度增加到70 ppm左右,可以提高采收率,但增加浓度会降低采收率。高于地层分离压力(FPP)的注入是有益的,但在高于FPP的注入过程中存在很高的不确定性,这可能会影响最终的原油采收率和净现值。研究结果表明,地质力学参数和岩石参数对模拟结果影响较大,在模拟过程中对其进行粗略估计会导致较大的误差和不确定性。此外,在模拟研究中精确地包括低盐度或智能水过程的主导机制是非常重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mechanistic Modeling of Low Salinity Water Injection under Fracturing Condition in Carbonate Reservoirs: Coupled Geochemical and Geomechanical Simulation Study
The main problem during field scale implantation of low salinity water injection (LSWI) is the decline in injectivity versus time. Moreover, the actual mechanisms that result in incremental oil recovery are not completely known. In previous studies, the geomechanical effects have not been considered, and pore volume changed while bulk volume is still constant which in turn can bring uncertainty to the simulation results. In this paper, both geochemical and geomechanical models have been coupled with the flow model. For coupling geomechanical model, three equations have been solved simultaneously in each time step. Then, the geochemical model has been coupled by adding the necessary aqueous and mineral reactions and ion concentration of both formation and injection waters. Increasing the Ca2+ concentration in the injected brine cause a reduction in the ultimate oil recovery. Also, increasing SO42− concentration in the injected brine up to about 70 ppm, resulted in increased oil recovery, while increasing the concentration caused a reduction in oil recovery. Injection above formation parting pressure (FPP) is beneficial but, there is a high uncertainty during injection above the FPP that can affect ultimate oil recovery and net present value. The results of this study show that geomechanical and rock parameters have intensive effects on the simulation results and rough estimating them in the simulation process can result in major errors and uncertainties. Further, it is very important to precisely include the dominant mechanisms of low salinity or smart water process during simulation studies.
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