Dynamic Fracture Characterization and Integrated Optimization of Enhanced Oil Recovery Performance in Tight Formations under Uncertainty

点击翻译按钮获取中文摘要

The primary recovery factor is very low (around 5-10%) for unconventional resources trapped in a tight formation, even after long horizontal wells have been drilled and massively fractured. Due to its rapid depletion on primary energy, enhanced oil recovery (EOR) methods are urgently needed to boost production; however, it is still a challenging task to increase the ultimate oil recovery because fluid flow in tight formations can be completely dependent on the fracture network while the matrix only plays a source role. Laboratory experiments and field tests have shown that waterflooding does not normally result in the expected performance as in the conventional reservoirs, that gas (e.g., hydrocarbon gas, CO2, and N2) injection, especially huff-n-puff processes, performs favourably, and that optimization of production-injection modes is found to be fundamentally important to exploit tight oil and shale gas reservoirs. Physically, fracture network, multiscale pore-throat/fracture structure and confined mass transfer make flow behaviour very complicated in tight formations. Furthermore, production or injection through a hydraulically fractured horizontal well leads to changes in the stress field, and hence induces changes in matrix permeability and fracture conductivity. Therefore, it is essential to integrally characterize fracture dynamics, determine residual oil saturation distribution within matrices and fractures, and optimize reservoir performance in the presence of geological and economic uncertainty for designing a technically feasible and economically sound EOR scheme and CO2 storage capacity in a tight formation. The major objectives of this proposed research are: 1) to experimentally and theoretically quantify phase behaviour and two-way mass transfer for the injected gases-light oil systems; 2) to perform network modelling of complex flow behaviour between matrix and fractures with the reconstructed pore-network obtained by using the micro-CT scanning images; 3) to develop an integrated inversion technique to characterize dynamic fracture network by performing transient pressure/rate analysis and matching production history together with monitoring and surveillance data; and 4) to develop robust and parallelized optimizers to efficiently optimize large-scale and closed-loop nonlinear systems in the presence of economic and geological uncertainty. Finally, we will provide the oil and gas industry with an integrated and pragmatic technique that can be applied to accurately quantify phase behaviour and fluid properties, characterize the dynamic fracture network, identify the underlying EOR mechanisms, and thus maximize oil recovery and CO2 storage capacity in tight formations with complex fracture networks under uncertainty in a cost-effective and sustainable manner.