Skauge, T. (CIPR Uni Research) | Skauge, A. (CIPR Uni Research) | Salmo, I. C. (CIPR Uni Research) | Ormehaug, P. A. (CIPR Uni Research) | Al-Azri, N. (PDO) | Wassing, L. M. (Shell Global Solutions International BV) | Glasbergen, G. (Shell Global Solutions International BV) | Van Wunnik, J. N. (Shell Global Solutions International BV) | Masalmeh, S. K. (Shell Global Solutions International BV)
Polymer injectivity is a critical parameter for implementation of polymer flood projects. An improved understanding of polymer injectivity is important in order to facilitate an increase in polymer EOR implementation. Typically, injectivity studies are performed using linear core floods. Here we demonstrate that polymer flow in radial and linear models may be significantly different and discuss the concept in theoretical and experimental terms.
Linear core floods using partially hydrolyzed polyacrylamides (HPAM) were performed at various rates to determine in-situ viscosity and polymer injectivity. Radial polymer floods were performed on Bentheimer discs (30 cm diameter, 2-3 cm thickness) with pressure taps distributed between a central injector and the perimeter production well. The in-situ rheological data are also compared to bulk rheology. The experimental set up allowed a detailed analysis of pressure changes from well injection to production line in the radial models and using internal pressure taps in linear cores.
Linear core floods show degradation of polymer at high flow rates and a severe degree of shear thickening leading to presumably high injection pressures. This is in agreement with current literature. However, the radial injectivity experiments show a significant reduction in differential pressure compared to the linear core floods. Onset of shear thickening occurs at significantly higher flow velocities than for linear core floods. These data confirm that polymer flow is significantly different in linear and radial flow. This is partly explained by the fact that linear floods are being performed at steady state conditions, while radial injections go through transient (unsteady state) and semi-transient pressure regimes.
History matching of polymer injectivity was performed for radial injection experiments. Differences in polymer injectivity are discussed in the framework of theoretical and experimental considerations. The results may have impact on evaluation of polymer flood projects as polymer injectivity is a key risk factor for implementation.
Enhanced oil displacement in a reservoir is highly affected by wettability alterations in conjunction with the lowering of viscosities during steam assisted gravity drainage (SAGD) for bitumen extraction. The impartation of energy in the form of heat to the fluid by injecting steam triggers an alteration to a more water-wet state during SAGD. However, the presence of three distinct phases in the reservoir has implications for the effective modeling of the complex fluid dynamics. Dependency of the relative permeability endpoints on the temperature realized as a function of the introduction of steam is difficult to model. Optimization of any steam process requires simulation in order to adequately characterize years of flow and so a model that is capable of representing three phase flow is necessary. To obtain this a pseudo-two phase relative permeability is proposed that assumes fractional flow theory is valid and treats the experiments as a waterflood.
In this study, experimental recovery data for two SAGD experiments and one hot water flood are empirically matched by manipulating relative permeabilities. The analytical approach implemented allows for the representation of fluid flow in the reservoir by achieving a pseudo-two phase relative permeability that results in comparable performance to the experiments. Waterflooding techniques were utilized which allowed for the negation of the steam phase in the model and so two-phase flow was established.
The sensitivity of the relative permeability curves to temperature change results in the inability to formulate a generic three-phase curve and so the pseudo-two phase curve is valuable for the purpose of simulation. The methodology presented enables the formulation of a simplified relative permeability that is unique to each process used and in that specific location. The model that was established was validated and proven credible by the good match with the experimentally obtained values.
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.
Fortenberry, R. (Ultimate EOR Services) | Delshad, M. (Ultimate EOR Services) | Suniga, P. (Ultimate EOR Services) | Koyassan Veedu, F. (DeGolyer & MacNaughton) | Wang, P. (DeGolyer & MacNaughton) | Al-Kaaoud, H. (Kuwait Oil Company) | Singh, B. B. (Kuwait Oil Company) | Tiwari, S. (Kuwait Oil Company) | Baroon, B. (Kuwait Oil Company) | Pope, G. A. (University of Texas at Austin)
Our team has developed a new simulation model for an upcoming 5-spot Alkaline-Surfactant-Polymer (ASP) pilot in the Sabriyah Mauddud reservoir in Kuwait. We present new pilot simulation results based on new data from pilot wells and an updated geocelluar reservoir model. New cores and well logs were used to update the geocellular model, including initial fluid distributions, permeability and layer flow allocation.
From the updated geocellular model a smaller dynamic sector model was extracted to history match field performance of a waterflood pattern. From the dynamic model a yet smaller pilot model was extracted and refined to simulate the 5-spot ASP pilot.
We used this pilot model to evaluate injection composition, zonal completions, observation well locations, interwell tracer test design and predicted performance of ASP flooding. A sensitivity analysis for some important design variables and pilot performance benchmarks is also included. We used multiple interwell tracer test simulations to estimate reservoir sweep efficiency for both water and ASP fluids, and to help us understand how well operations will affect this unconfined ASP pilot. This work details some crucial aspects of pre-ASP pilot design and implementation.
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.
Erke, S. I. (Salym Petroleum Development) | Volokitin, Y. E. (Salym Petroleum Development) | Edelman, I. Y. (Salym Petroleum Development) | Karpan, V. M. (Salym Petroleum Development) | Nasralla, R. A. (Shell Global Solutions International) | Bondar, M. Y. (Salym Petroleum Development) | Mikhaylenko, E. E. (Salym Petroleum Development) | Evseeva, M. (Salym Petroleum Development)
Low-salinity waterflooding (LSF) has been recognized as an IOR/EOR technique for both green and brown fields in which the salinity of the injected water is lowered for particular reservoir properties to improve oil recovery. While providing lower or similar UTC's low salinity projects have the advantage of lower capital and operational costs as compared to some more expensive EOR alternatives.
This work describes LSF experiments, field-scale simulation results, and conceptual design of surface facilities for West Salym oil field. The field is located in West Siberia and is on stream since 2004. Conventional waterflooding was started in 2005 and current water cut is currently above 80% in the developed area of the field. To counter oil production decline a tertiary Alkaline-Surfactant-Polymer (ASP) flooding technique selected for mature waterflooded field parts and piloting of this technique is ongoing. Operationally simpler and more cost-effective LSF method is considered for implementation in the unflushed (green) areas of the field since it has been recognized that application of LSF in secondary mode results in better incremental oil recovery than LSF in tertiary mode.
The results of a comprehensive conceptual study performed to justify the LSF trial are presented in this paper. To generate production forecast for LSF in the isolated area at the outset of reservoir development the results of laboratory core tests executed at different salinities presented earlier (
Rodriguez, F. (PDVSA, IFP Energies nouvelles, Paris Diderot University) | Rousseau, D. (IFP Energies nouvelles) | Bekri, S. (IFP Energies nouvelles) | Hocine, S. (Solvay) | Degre, G. (Solvay) | Djabourov, M. (ESPCI Paris Tech) | Bejarano, C. A. (PDVSA)
Primary cold production for the extra-heavy oils (4–10°API) of La Faja Petrolifera del Orinoco (FPO), Venezuela, is currently a low percentage (<5%) of the OOIP. Chemical EOR (CEOR) studies are being accomplished in order to increase oil recovery in those thin-bedded reservoirs which host up to 35% of the OOIP, where thermal EOR methods are not convenient because of heat losses and environmental issues. Specifically, Surfactant-Polymer (SP) flooding is now considered as a feasible approach to achieve both mobility control and mobilization of residual oil in the FPO's target zones for CEOR.
The objectives of this experimental study were to identify some mechanisms in play when surfactant and polymer solutions are injected in cores to displace extra-heavy oil and to assess for the potential of SP flooding for one of the FPO's reservoirs. The tests reported were performed with a dead crude oil of 9°API and 4500 cP, and injection water salinity of 6.4 g/L with low hardness and at a temperature of 50°C. The SP formulation consisted of a standard high molecular weight HPAM at rather high concentration to achieve high viscosity and an alkaline-free surfactant formulation providing both low interfacial tension (IFT) and good compatibility with polymer even at high polymer concentration. When possible, oil saturation profiles were determined by CT-scan at the main steps of the experiments.
Conditions and methodologies to determine the relevant experimental parameters for high viscosity oil have firstly been developed. Then, a set of surfactant and polymer injection tests have been performed on Bentheimer outcrop cores. These tests demonstrated that injection of the SP formulation after a secondary polymer flood was able to achieve a significant reduction of the residual oil (ASo = 80% ROIP). Results of secondary injections of water (final oil saturation, Sofinal = 63%), surfactant solution (Sofinal = 39%) and SP formulation (Sofinal = 5%) have also shown that mobility control is of tremendous importance to achieve high recovery, even at the core-scale. The potential of the SP formulation has also been validated on unconsolidated reservoir rock material from the FPO (Sofinal = 8%). Relative permeabilities have also been determined to investigate the feasibility of an effective modeling of the impact of the surfactant on oil recovery without making any assumption of the local mechanisms in play. Future work will involve 3D reservoir simulation with physico-chemical parameters generated at the lab.
Jong, Stephen (University of Texas at Austin) | Nguyen, Nhut M. (University of Texas at Austin) | Eberle, Calvin M. (University of Texas at Austin) | Nghiem, Long X. (Computer Modelling Group Ltd.) | Nguyen, Quoc P. (University of Texas at Austin)
Low Tension Gas (LTG) flooding is a novel EOR process which can address challenging reservoir conditions such as high salinity, high temperature, and tight rock. Current process understanding is limited, and a joint experimental and modeling approach allows for both interpretation and insight into the complex interactions between the key process parameters of salinity gradient, foam strength, microemulsion phase behavior, and phase desaturation in order to achieve a physically correct and predictive process model.
We performed a series of corefloods in high permeability Berea sandstones (~500 mD) to demonstrate the impact of salinity gradient on the LTG process and interactions between key mechanisms such as microemulsion phase behavior and foam stability. In order to provide additional insight into the experimental study and improve understanding of the LTG process, we used our newly developed LTG simulator which we built within CMG GEM.
The results demonstrate that decreasing slug injection salinity can lead to a 15% increase in residual oil in place (ROIP) recovery over a slug injected at optimum salinity, with earlier breakthrough and steeper recovery slope. In addition, there is evidence of a late time pressure buildup as salinity is decreased through mixing with drive salinity which is indicative of increasing foam stability. This may be due to an inverse relationship between oil-water IFT and foam stability and thus designing an optimal salinity gradient for an LTG process requires balancing oil mobilization due to ultralow IFT and effectively displacing mobilized oil with adequate foam mobility control.
We introduce and show the strength our compositional LTG simulator in a pioneering laboratory and simulation study that sheds light on the interaction between salinity, microemulsion phase behavior, and foam strength. Our conclusions indicate a significant departure from traditional ASP understanding and methodology when designing an LTG salinity gradient and serve as a foundation for future investigation.
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.
Pilots are widely used for the purpose of gathering valuable information about performance and practical challenges of implementing a particular CEOR process in a given field (
Addition of chemical species to the material balance equations alongside finer resolution requirements for CEOR simulations compared to waterfloods (WF), often make it impractical to run full field CEOR simulations to the required accuracy. Massively parallel computing, dynamic local grid refinement and sector modeling have been used with varying success, of which sector modeling is the most common. Sector models, by their very definition, are also naturally suited for modeling of pilots.
The art of sector modeling needs mastering a few important steps such as: appropriate selection of the sector model extent, details on carving it out of the Full Field Model (FFM), populating it with proper petrophysical and fluid properties, initializing it to correct initial conditions and optimizing its boundary conditions. On top of that, choice of optimum grid size for proper trade-off of simulation run times and accuracy needs to be considered.
This paper presents a case study for appropriate simulation of a CEOR pilot within Chevron. The candidate has a waterflood history matched FFM. This model is used to generate a sector model for the CEOR pilot area. This paper outlines how the extent of the sector model and all the regions in communication with the Area of Interest (AOI) is decided. It also discusses proper initialization and optimization of the boundary conditions of the sector model along with its appropriate refinement and grid optimization. Proper CEOR simulations on the final optimized sector model and sensitivity analysis are also presented. The challenges, lessons learned and best practices are shared and important considerations for adequate simulation of CEOR processes are outlined.