This paper addresses two questions for polymer flooding. First, what polymer solution viscosity should be injected? A base-case reservoir-engineering method is present for making that decision, which focuses on waterflood mobility ratios and the permeability contrast in the reservoir. However, some current field applications use injected polymer viscosities that deviate substantially from this methodology. At one end of the range, Canadian projects inject only 30-cp polymer solutions to displace 1000-3000-cp oil. Logic given to support this choice include (1) the mobility ratio in an unfavorable displacement is not as bad as indicated by the endpoint mobility ratio, (2) economics limit use of higher polymer concentrations, (3) some improvement in mobility ratio is better than a straight waterflood, (4) a belief that the polymer will provide a substantial residual resistance factor (permeability reduction), and (5) injectivity limits the allowable viscosity of the injected fluid. At the other end of the range, a project in Daqing, China, injected 150-300-cp polymer solutions to displace 10-cp oil. The primary reason given for this choice was a belief that high molecular weight viscoelastic HPAM polymers can reduce the residual oil saturation below that expected for a waterflood or for less viscous polymer floods. This paper will examine the validity of each of these beliefs.
The second question is: when should polymer injection be stopped or reduced? For existing polymer floods, this question is particularly relevant in the current low oil-price environment. Should these projects be switched to water injection immediately? Should the polymer concentration be reduced or graded? Should the polymer concentration stay the same but reduce the injection rate? These questions are discussed.
This paper presents the basic reservoir characteristics and the key improved oil recovery/enhanced oil recovery (IOR/EOR) methods for sandstone reservoir fields that have achieved recovery factors toward 70%. The study is based on a global analog knowledge base and associated analytical tools. The knowledge base contains both static (STOIIP, primary and ultimate recovery factors, reservoir/fluid properties, well spacing, drive mechanism, and IOR/EOR methods etc.) and dynamic data (oil rate, water-cut, and GOR, etc.) for more than 730 sandstone oil reservoirs. These reservoirs were subdivided into two groups: heavy and conventional oil reservoirs. This study focuses on the reservoirs with recovery factors great than 50% for heavy oil, and recovery factors from 60% to 79% for conventional oil with a view to understand the key factors for such a high recovery efficiency. These key factors include reservoir and fluid properties, wettability, development strategies and the IOR/EOR methods.
The high ultimate recovery factors for heavy oil reservoirs are attributed to excellent reservoir properties, horizontal well application, high efficiency of cyclic steam stimulating (CSS) and steam flood, and very tight well spacing (P50 value of 4 acres, as close as 0.25 acres) development strategy. The 51 high recovery conventional clastic reservoirs are characterized by favorable reservoir and fluid properties, water-wet or mixed-wet wettability, high net to gross ratio, and strong natural aquifer drive mechanism. Infill drilling and water flood led to an incremental recovery of 20% to 50%. EOR technologies, such as CO2 miscible and polymer flood, led to an incremental recovery of 8% to 15%. Homogeneous sandstone reservoirs with a good lateral correlation can reach 79% final recovery through water flood and adoption of close well spacing.
The lessons learned and best practices from the global analog reservoir knowledge base can be used to identify opportunities for reserve growth of mature fields. With favorable reservoir conditions, it is feasible to move final recovery factor toward 70% through integrating good reservoir management practices with the appropriate IOR/EOR technology.
Dwarakanath, Varadarajan (Chevron) | Dean, Robert M. (Chevron) | Slaughter, Will (Chevron) | Alexis, Dennis (Chevron) | Espinosa, David (Chevron) | Kim, Do Hoon (Chevron) | Lee, Vincent (Chevron) | Malik, Taimur (Chevron) | Winslow, Greg (Chevron) | Jackson, Adam C. (Chevron) | Thach, Sophany (Chevron)
Polymer flooding by liquid polymers is an attractive technology for rapid deployment in remote locations. Liquid polymers are typically oil external emulsions with included surfactant inversion packages to allow for rapid polymer hydration. During polymer injection, a small amount of oil is typically co-injected with the polymer. The accumulation of the emulsion oil near the wellbore during continuous polymer injection will reduce near wellbore permeability. The objective of this paper is to evaluate the long-term effect of liquid polymer use on polymer injectivity. We also present a method to remediate the near well damage induced by the emulsion oil using a remediation surfactant that selectively solubilizes and removes the near wellbore oil accumulation. We evaluated several liquid polymers using a combination of rheology measurement, filtration ratio testing and long-term injection coreflood experiments. The change in polymer injectivity was quantified in surrogate core after multiple pore volumes of liquid polymer injection. Promising polymers were further evaluated in both clean and oil-saturated cores. In addition, phase behavior experiments and corefloods were conducted to develop a surfactant solution to remediate the damage induced by oil accumulation. Permeability reduction due to long term liquid polymer injection was quantified in cores with varying permeabilities. The critical permeability where no damage was observed was identified for promising liquid polymers. A surfactant formulation tailored for one of the liquid polymers improved injectivity three- to five-fold and confirms our hypothesis of permeability reduction due to emulsion oil accumulation. Such information can be used to better select appropriate polymers for EOR in areas where powder polymer use may not be feasible.
The polymer pilot project performed in the 8 TH reservoir of the Matzen field showed encouraging incremental oil production. To further improve the understanding of recovery effects resulting from polymer injection, an extension of the pilot is planned by adding a second polymer injector.
Forecasting of the incremental oil production needs to take the uncertainty of the geological models and dynamic parameters into account. We propose a workflow which comprises a geological sensitivity and clustering step followed by a dynamic calibration step for decreasing the objective function to improve the reliability of a probabilistic forecast of the incremental oil recovery.
For the geological sensitivity, hundreds of geological realizations were generated taking the uncertainty in the correlation of the sand and shale layers, logs, cores and geological facies into account. The simulated tracer response was used as dissimilarity distance to classify the geological realizations. Clustering was then applied to select 70 representative realizations (centroids) from a total of 800 to use in the full-physics dynamic simulation.
In the dynamic simulation, an objective function comprising liquid rate and tracer concentration of the back-produced fluids was introduced.
To further improve the calibration, the P50 value of incremental oil production as derived from simulation was compared with the incremental oil production determined from Decline Curve Analysis from the wells surrounding the polymer injection well. The mismatch between the P50 and the Decline Curve Analysis was improved by adjusting polymer viscosity.
The calibrated models were then used to for a probabilistic forecast of incremental oil due to an additional polymer injector and to estimate the expected polymer concentration at the producing wells.
Luo, Haishan (The University of Texas at Austin) | Mohanty, Kishore K. (The University of Texas at Austin) | Delshad, Mojdeh (The University of Texas at Austin) | Pope, Gary A. (The University of Texas at Austin)
Upscaling of unstable immiscible flow remains an unsolved challenge for the oil industry. The absence of a reliable upscaling approach greatly hinders the effective reservoir simulation and optimization of heavy oil recoveries using waterflood, polymer flood and other chemical floods, which are inherently unstable processes. The difficulty in upscaling unstable flow lies in estimating the propagation of fingers smaller than the gridblock size. Using classical relative permeabilities obtained from stable flow analysis can lead to incorrect oil recovery and pressure drop in reservoir simulations.
In a recent study based on abundant experimental data, it is found that the heavy-oil recovery by waterfloods and polymer floods has a power-law correlation with a dimensionless number (named viscous finger number in this paper), which is a combination of viscosity ratio, capillary number, permeability, and the cross-section area of the core. Based upon this important finding as well as the features of unstable immiscible floods, an effective-finger model is developed in this paper. A porous medium domain is dynamically identified as three effective zones, which are two-phase flow zone, oil single-phase flow zone, and bypassed oil (isolated oil island) zone, respectively. Flow functions are derived according to effective flows in these zones. This new model is capable of history-matching a set of heavy-oil waterflood corefloods under different viscosity ratios and injection rates. Model parameters obtained from the history match also have a power-law correlation with the viscous finger number.
The build-up of this correlation contains reasonable physical meanings to quantitatively characterize the upscaled behavior of viscous fingering effects. Having such a correlation enables the estimation of model parameters in any gridblock of the reservoir by knowing the local viscous finger number in reservoir simulations. The model is applied to several heavy-oil field cases with waterfloods and polymer floods with different heterogeneities. Oil recovery in water flooding of viscous oils is overpredicted by classical simulation methods which do not incorporate viscous fingering properly. Simulation results indicate that the new model reasonably differentiates the oil recoveries at different viscous finger numbers, e.g., lower injection rate leads to higher oil recovery. In contrast, classical simulations obtain close oil recoveries under different injection rates or degrees of polymer shear-thinning, which is apparently incorrect for unstable floods. Moreover, coarse-grid simulations using the new model are able to obtain consistent saturation and pressure maps with fine-grid simulations when the correlation lengths are not smaller than the coarse gridblock size. Furthermore, it is well captured by the model that the shear-shinning polymer solution can strengthen the fingering in high-permeability regions due to increased capillary number and viscosity ratio, which is not observed in waterflood. As a whole, the new model shows encouraging capability to simulate unstable water and polymer floods in heavy oil reservoirs, and hence can facilitate the optimization of heavy-oil EOR projects.