Tracking Interwell Water Saturation in Pattern Flood Pilots in a Giant Gulf Oil field

Abstract

Peripheral water flooding has been the preferred pressure maintenance tool for many gulf carbonate reservoirs over the past 30 years. Due to uneven sweep and pressure distribution, this technique has given way to pattern floods in several gulf fields. As these new floods are established, it is important to understand the water saturation between wells to properly manage the sweep and recovery. In 2007, ADCO initiated water injection (WI) and WAG pilots to test the recovery strategy. The pilot employs advanced geophysical and modeling tools to measure formation properties at the wells and between wells; this paper discusses the WI pilot. Among the novel techniques applied is the crosswell electromagnetic method, which measures the interwell resistivity distribution between observation wells at the pilots. Interwell resistivity data can be used to infer the water saturation distribution because of the sharply different electrical resistivity between injected water and oil bearing reservoir rock. By allowing an evaluation of the water distribution long before the injected fronts reach producers or observers, a better and more rapid understanding of the pilot arises from the crosswell electromagnetic technique. In this paper, we briefly describe the pilot design, describe the detailed geological model and show results from the initial set of baseline and time lapse EM data sets from the water injection pilot. The images highlight the influence of background geological constraints on the flow. Introduction Applying peripheral water flooding for pressure maintenance was commenced after few years of the discovery of field A, a giant complex carbonate reservoir in the middle-east. Although this strategy has been successful, there is evidence of an uneven sweep due to reservoir complexity. These complications have led to the introduction of pattern-based flooding technology and the establishment of the water injection (WI) and WAG pilots in the underswept lower units of the reservoir. The benefits of pattern flooding are more efficient and faster recovery. The potential drawbacks are greater costs and higher local pressures which could induce uneven flows. Detailed pattern flood modeling helped develop an optimum strategy for maximizing reserves and production, especially in the lower two oil bearing units of the reservoir (Ref. 1). Consequently, WI pilot has been implemented in the lower units of the reservoir. A detailed multi-year and multi measurement monitoring plan has been established to determine the pilot performance which includes deep reading technologies like electromagnetic surveys. The main objectives of the WI pilot project are:determine sweep efficiency in the target reservoir units,qualitatively assess the impact of injected fluid fluxes vertically across low permeability sub-units within the reservoir, anddetermine pressure support due to pattern injection. The pilot will also address the issues of uneven sweep, bypassed oil, and residual oil saturation. The acquired field data will be used to calibrate the simulation model for production, injection, saturation and pressure data in order to design as an optimum field development scheme for the lower reservoir units in the southern part of the field. (Ref 2)

Practical Applications of Time-lapse Seismic Data

“…Crosswell resistivity mapping has been used to monitor water injection in several geologic settings, including in a diatomite reservoir in California (Wilt et al, 2005) and in carbonate fields in the Middle East (Bhatti et al, 2008;Marsala et al, 2008). An example from Oman (Mieles et al, 2009) is shown in Figure 10.…”

Simultaneous estimation of permeability and porosity from joint inversion of time-lapse seismic, electromagnetic, and production data

“…Time-lapse crosswell electromagnetic has been applied for tracking interwell fluid movement (Hoversten et al, 2001;Wilt and Alumbaugh, 2001;Bhatti et al, 2008). Time-lapse controlled-source electromagnetic (CSEM) has also been explored for reservoir monitoring applications (Lien and Mannseth, 2008;Orange et al, 2009;Black et al, 2010;Shahin et al, 2010;Berre et al, 2011;Liang et al, 2011b;Andreis and MacGregor, 2011).…”