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

不确定性条件下致密地层动态裂缝表征及提高采收率综合优化

• 批准号: RGPIN-2019-07150
• 负责人: Yang, Daoyong
• 金额: $ 2.84万
• 依托单位: University of Regina
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=715651
• 关键词: Dynamic; Fracture; Characterization; Integrated; Optimization

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.

对于被困在紧密地层中的非常规资源的主要恢复因子（约为5-10％），即使经过长时间的水平井进行了钻孔和大规模破裂。由于其对初级能量的快速耗竭，迫切需要增强的石油回收（EOR）方法来增强生产。但是，增加最终的石油回收率仍然是一项具有挑战性的任务，因为紧密地层中的流体流可以完全取决于断裂网络，而矩阵仅扮演源角色。实验室实验和现场测试表明，水中通常不会像常规储层那样导致预期的性能，例如，气体（例如，碳氢化合物气体，二氧化碳和N2）注入，尤其是Huff-N-Puff过程，并且表现出色，并且表现出色，并且表现出色，并且表现出色。人们发现，对生产注射模式的优化对于开发紧密的油和页岩气储层至关重要。从物理上讲，断裂网络，多尺度毛孔 - 毛刺/断裂结构和狭窄的传质使流动行为在紧密的地层中非常复杂。此外，通过液压骨折的水平井的生产或注射会导致应力场的变化，从而引起基质渗透性和断裂电导率的变化。因此，重要的是要整合骨折动态，确定矩阵和断裂内的残留油饱和度分布，并在存在地质和经济不确定性的情况下优化储层性能，以设计技术可行且经济上可行的EOR方案和CO2存储能力形成。 这项拟议的研究的主要目标是：1）对注射气体油系统的实验和理论上量化相行为和双向传质； 2）使用Micro-CT扫描图像获得了重建的孔网，对矩阵和断裂之间的复杂流动行为进行网络建模； 3）开发一种集成的反转技术来通过执行瞬态压力/速率分析和匹配生产历史记录以及监视和监视数据来表征动态断裂网络； 4）在存在经济和地质不确定性的情况下，开发健壮和并行的优化器，以有效地优化大型和闭环非线性系统。最后，我们将为石油和天然气行业提供一种集成且务实的技术，可用于准确量化相位行为和流体特性，表征动态断裂网络，识别基本的EOR机制，从而最大化石油回收率和CO2存储能力在与复杂的裂缝网络的紧密地层中，以成本效益和可持续性的方式在不确定的情况下。