通过各种数据采集活动,为大型注水油藏优化历史匹配质量,以释放其最大采收率潜力:一个案例研究

I. Jamaludin, D. Mandal, D. Arsanti, Izyan Nadirah Dzulkifli, N. A. Zakaria, Salhizan Mohamad Salleh, Saiful Adli Ahmad Hawari, M. Azkah
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引用次数: 0

摘要

数据采集仍然是任何油田开发过程中始终执行的关键活动之一。每年都会分配大量的运营支出(OPEX)来了解储层的动态,从而减少不确定性并实现优化。本文旨在强调在水驱油藏模拟模型历史匹配(HM)过程中面临的问题,包括对沉积环境的理解和生产数据的完整性。利用产出来提高采收率(RF),通过增加注水机会和优化注水。A油田在2006年进行了第二次三维地震拍摄(1995年第一次),并将其处理成延时4D地震。2014年,利用高精度温度、频谱噪声测井(HPT-SNL)工具完成了套管井测井,检查了x油藏12口井的完整性和流量贡献。在同一时期,进行了脉冲压力测试(PPT),以验证井间的通信,此外还获得了定期监测数据,有助于改进储层模拟研究。4D地震有助于了解区域水驱前缘运动,并解释了上倾井的含水趋势异常,该井比下倾井更早见水。此外,它还有助于确定一个可能成为充填位置的旁路油区。由于大多数井采用双管柱完井,HPT-SNL作业有助于改善多层叠储层的产量分配,并识别出需要整改的问题井。PPT帮助确定了一个挡板区,以解释附近注水井在南部一些生产商观察到的低压力支撑。所有数据解释都被纳入最终的HM模型,该模型随后确定了充填位置,并成功修改了油藏管理计划(RMP)。2015年,该公司实施了一项填充计划,成功地获得了约900万美元的额外收益。根据研究和结果,通过优化孔隙替代比(VRR)和采油者(OP)到注水井(WI)的转换,注水优化有助于提高产量,增加了约200万stb的储量。通过这些努力,团队可以成功地预测RF >55%。本案例研究展示了如何获取重点监测数据并将其有效整合到模拟研究中的性能分析中,有助于减少不确定性,揭示填充机会,改善生产注入优化,从而有助于提高棕色油田的采收率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Refining History Matching Quality through Various Data Acquisition Campaign for a Major Waterflood Reservoir to Unleash Its Maximum Recovery Potential: A Case Study
Data acquisition remains one of the crucial activities to be consistently executed throughout field life for any oilfield development. Significant operating expenditure (OPEX) is allocated each year to understand reservoir performance, thus reduce uncertainties and enable optimizations. This paper aims to highlight the issues faced during simulation model history matching (HM) process of a waterflood reservoir, including understanding of depositional environment and production data integrity. The output is utilized to improve recovery factor (RF) via infill opportunities and water injection optimization. Field A has run a second shot of 3D seismic in 2006 (first in 1995) and processed into a time lapse, 4D seismic. In 2014, a cased hole logging campaign utilizing the high precision temperature, spectral noise logging (HPT-SNL) tool has been completed to check the integrity and flow contribution of 12 wells in Reservoir-X. Within the same period, a pulse pressure testing (PPT) was carried out to verify the communication between wells, in addition to acquiring regular surveillance data which helped to improve reservoir simulation study. The 4D seismic helped to understand the areal waterflood front movement and explained the water cut trend anomaly in an updip well which experienced earlier water breakthrough than near downdip producers. Moreover, it helped to identify a bypass oil zone which can potentially be an infill location. As most of the wells are on dual string completion, the HPT-SNL campaign helped to improve production allocation of multi stacked reservoirs as well as identify problematic wells which required rectification jobs. The PPT assisted in identifying a baffle zone to explain the poor pressure support observed in some producers in the south from the nearby water injectors. All data interpretations were incorporated into final HM model which subsequently identified infill locations and the reservoir management plan (RMP) was successfully revised. An infill program was executed in 2015, which successfully secured additional EUR of ~9 MMstb. Based on the studies and outcome of the infill campaign water injection optimization helped to improve production and added ~2 MMstb reserves, through voidage replacement ratio (VRR) optimization and oil producer (OP) to water injector (WI) conversion. With these efforts, team could successfully project RF of >55%. This case study demonstrates how acquiring focused surveillance data and their effective integration in performance analysis in simulation study helps to reduce uncertainties, unveils infill opportunities, improves production injection optimization and thus helps to improve the recovery factor in brown fields.
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