Abstract

Summary It is well-known that water injection may induce formation fracturing in tight reservoirs. Especially when the field-geology condition is complex and the waterflood-induced fractures (WIFs) are not well-identified in time, the induced fractures can be of the same order as the well spacing, which has a significant, and generally undesired, impact on both areal sweep and vertical conformance. Therefore, the onset of WIFs must be identified in a timely manner, and the waterflooding performance must be evaluated comprehensively to formulate an appropriate strategy over time. A new work flow, containing analytical/semianalytical, statistical, and numerical techniques that are based on flow-rate/BHP and formation-testing data, is applied to identify the WIFs, diagnose waterflooding direction and front distribution, analyze interwell connectivity, and interpret abnormal bottomhole-pressure (BHP) behaviors in the Changqing Oil field. The work flow includes three modules: First, real-time monitoring and analysis, including modified Hall plot, evolving skin analysis, and injection/fracturing index methods, are used to identify the start of WIFs. Then, the formation-testing module, consisting of step-rate test (SRT), radioactive-tracer logging, and passive seismic method, is applied to investigate the formation-fracturing pressure, and uneven waterflooding performance in the areal and vertical directions. On the basis of the two former modules, we adapt the third module, which includes injector/producer relationships (IPRs) and the constrained multiple-linear-regression (MLR) method, to quantitatively investigate the waterflooding direction by injection/production rates. A new model—injection well with waterflood-induced fracture (IWWIF)—is proposed to characterize the abnormal BHP behaviors considering the properties variation (shrinking fracture length and decreasing fracture conductivity) of WIFs during the falloff period. Compared with an individual method, the ITD (which is the abbreviation of WIF identification, formation testing, and dynamic production analysis) work flow is developed to obtain a comprehensive and deep understanding of waterflooding performance. The main emphasis of this study is to integrate different approaches to address the key uncertainties rather than analyze each data source individually. On the basis of the results obtained by this work flow, the operators can make a more-proactive and -reasonable decision on waterflooding management. The work flow proposed in this paper gives a useful guidance in short- and long-term waterflooding management in tight reservoirs.

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