Given limited CO2 supply, operational constraints, and pattern specific reservoir performance, WAG schedule can be customized such that NPV or other metrics are optimized. Depending on the WAG schedule, recovery can fluctuate between 5–15% at the pattern scale due to reservoir heterogeneity causing variations in sweep efficiency. An analytical method was developed to optimize WAG schedules that couples traditional reservoir modeling and simulation with machine learning, enabling the discovery of optimal WAG schedules that increase recovery at the pattern level. A history-matched reservoir model of Chaparral Energy's Farnsworth Field, Ochiltree County, TX was sampled intelligently to perform predictive reservoir flow simulations and artificially build an intelligent reservoir model that samples a broad range of possible WAG scenarios for optimization. The intelligent model generates the next "best" sample to investigate in the numerical simulator and converges on the optima, quickly reducing the number of runs investigated. Results in this paper demonstrate that there can be significant improvements in net present value as well as net utilization rates of CO2 using this analytical technique. The WAG design generated by the intelligent reservoir model should be deployed in the field in early 2016 for validation. It is intended that the intelligent reservoir model will be updated on a regular basis as injection and production data is obtained. This effort represents the beginning of a paradigm shift in the application of modeling and simulation tools for significant improvements in field production operations.
Lee, Jason (University of Pittsburgh) | Dhuwe, Aman (University of Pittsburgh) | Cummings, Stephen D. (University of Pittsburgh) | Beckman, Eric J. (University of Pittsburgh) | Enick, Robert M. (University of Pittsburgh) | Doherty, Mark (GE Global Research) | O'Brien, Michael (GE Global Research) | Perry, Robert (GE Global Research) | Soong, Yee (US DOE NETL) | Fazio, Jim (US DOE NETL) | McClendon, Thomas R. (US DOE NETL)
CO2 miscible and immiscible displacements and hydrocarbon miscible floods are commonly plagued by low volumetric sweep efficiency, early gas breakthrough, high gas utilization ratios, and significant gas re-compression and recycle. Rather than addressing these problems via the water-alternating-gas (WAG) injection sequence that reduces gas relative permeability or the generation of gas-in-brine foams for reduced mobility, we propose increasing the viscosity of high pressure CO2 or NGL via the dissolution of dilute concentrations of thickening agents.
There are two strategies for increasing the viscosity of high pressure fluids; the dissolution of ultrahigh molecular weight polymers or associating polymers, or the dissolution of small molecules that self-assemble in solution to form viscosity-enhancing linear or helical supramolecular structures. Ideally a very small amount of the thickener will be required (roughly 0.1wt%) to elevate the CO2 or NGL viscosity to the same value as the oil being displaced (typically a 10-100 fold increase). Further, the thickened CO2 or thickened NGL should be a stable, transparent solution that does not require a heating/cooling cycle for viscosity enhancement to occur.
Thickener solubility and viscosity were determined over a 25-100oC range. Each of the three major NGL constituents (ethane, propane and butane) was thickened with an ultrahigh molecular polymer (commercial drag reducing agent), resulting in a 2-30 fold increase in viscosity at polymer concentrations of 0.5wt% or less. The polymer dissolved at the lowest pressure in butane and was most effective as a thickener in butane.
Three small molecule thickeners were identified for the NGL constituents; tri-alkyl-tin fluoride, hydroxyaluminum disoap, and a phosphate ester-crosslinker mixture. Remarkable viscosity enhancements were attained for propane and butane with the tri-alkyl-tin fluoride and aluminum soap; the crosslinked phosphate ester solutions exhibited modest viscosity increases. Only tri-alkyl-tin fluoride thickened ethane.
CO2 thickeners were assessed with a falling ball viscometer and pressure drop associated with flow through Berea sandstone. 4-5 fold increases in viscosity were attained with 1wt% of a high molecular weight polyfluoroacrylate. 3-4 fold increases in viscosity were attained with 1wt% high molecular weight polydimethyl siloxane, but a very large amount of toluene co-solvent was required. Although a remarkably effective small molecule thickener was designed for CO2 (100-fold increase at 1.3wt%), it required a heating/cooling cycle and a very large amount of hexane co-solvent.
We have identified the first polymeric and small molecule thickeners ever reported for ethane. Further, this study presents the largest viscosity increases ever reported for propane and butane with polymers and small molecule thickeners. We have presented the most effective polymeric thickeners for CO2 reported to date. This paper also summarizes numerous molecular architectures that are not viable for CO2 and highlights the most promising compounds that continue to be refined.
Depth to Surface Resistivity (DSR) has been shown to be effective at mapping CO2, water flood, and residual oil aerially and vertically. Provided there is sufficient resistivity contrast between injected and in-situ fluids and subject to the reservoir depth and overburden resistivity, the technique is applicable for monitoring IOR/EOR fields. This information can be used to evaluate cap rock integrity, fluid loss to faults, and migration paths. The following paper presents a study of a CO2 flood followed by water alternating gas (WAG) injection.