A Novel Water-Injectivity Model and Experimental Validation With CT-Scanned Corefloods
- Ramesh Chandra Yerramilli (The University of Texas at Austin) | Pacelli L. J. Zitha (Delft University of Technology) | Sanjay Surya Yerramilli (The University of Texas at Austin) | Pavel Bedrikovetsky (The University of Adelaide)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- December 2014
- Document Type
- Journal Paper
- 1,200 - 1,211
- 2015.Society of Petroleum Engineers
- laboratory experiments, waterflooding, particle size distribution, injectivity model , solids retention
- 1 in the last 30 days
- 399 since 2007
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Injectivity decline is an issue during produced-water reinjection (PWRI) for water disposal in aquifers, waterflooding, chemical enhanced oil recovery, and geothermal-energy exploitation. A novel model for injectivity decline under flow conditions reminiscent of PWRI was developed taking into account deep-bed-filtration and buildup of external filter cake. A distinct feature of the model is that it describes particle-retention kinetics responsible for internal filtration by an exponential decaying function of the retained-particle concentration. The corresponding nonlinear governing partial-differential equations were solved numerically and coupled with a known analytical model for external filtration with the concept of transition time. Coreflood experiments consisting of the injection of brine containing suspended hematite particles (volume fractions in the range of 2 to 6 ppm) were also performed. Computed-tomography (CT) scans of the core were taken to obtain deposition profiles along the core at different times. In addition, effect of various parameters (particle concentration and number of grids) on injectivity was investigated. From CT-scan and optical-microscope analyses, it was found that surface deposition in the porous medium and face plugging at the injection face of the core were responsible for decline in injectivity. The transition time from pure internal to external filtration was accurately determined from the CT-scan and pressure data. The newly proposed model and experiments were found to be in excellent agreement, indicating that the adopted retention function is a good heuristic description of particle retention.
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