This work presents a new workflow to obtain a better-constrained reservoir-scale model for an Alkaline-Surfactant-Polymer (ASP) injection pilot design. It is explained how the impact of uncertain parameters related to ASP flooding can be quantified, using calibrated core-scale simulation based on experimental results, and how the influential parameters range for future reservoir-scale simulation can be determined. Computational costs of core-scale model are therefore much lower, and the final reservoir model is better constrained. ASP flooding feasibility implies core scale studies, where chemical formulations are validated in the laboratory under field conditions. In the objective of the pilot designing, a numerical model is constructed and calibrated to history-match the core flood sequences: Remaining Oil Saturation (ROS), surfactant-polymer (SP) and polymer-alkaline (PA) injection and eventually the chase water slug. In order to quantify the impact of ASP chemical parameters on the history match, the Global Sensitivity Analysis (GSA) was performed using Response Surface Modeling (RSM). To obtain the acceptable range of influential parameters for future reservoir-scale simulation, the Bayesian optimization is used. Applying this methodology on a real reservoir core, the laboratory measurements are accurately reproduced. Nevertheless, once the core-scale model was matched, the transition to reservoir-scale model must be done. Due to a large number of parameters and their associated uncertainties, this transition is not straight-forward. Thus, an additional step in our workflow is included. A new methodology is applied to firstly quantify the impact of uncertain parameters related to ASP flooding (adsorption of surfactant on the rock, critical micellar concentration, water mobility reduction by polymer etc.). To do so, the RSM is used and influential parameters are identified. In this study, the surfactant adsorption coefficients are the most influential parameters while others related to SPA have a poor impact on experiment results matching. Secondly, the acceptable range of influential parameters for future reservoir-scale simulation and feasibility study is obtained during Bayesian optimization. Thus, instead of using a wide (prior) range of uncertain parameters values, refined (posterior) distribution laws can be used for future reservoir model. While the classical approach consists in matching experimental results to obtain calibrated values of certain properties (that are then entered in the reservoir model) and finally determine the influential parameters at the reservoir scale, here the choice was made to determine influential parameters and characterize their impacts at the core scale. This step helps to better constrain the reservoir model. Ongoing work is using the results of this workflow for pilot design and risk analysis.

Geothermal energy development is of critical importance to meet the global challenge of energy transition. This work demonstrates that existing oil and gas industry tools can be used to evaluate the potential of geothermal energy production from mature oilfields using the heat contained in the produced fluids. This can contribute to a decarbonation strategy and be profitable since most of the costs (drilling, pumps…) are already supported by oil production operations. The only additional costs consist in surface facilities to convert thermal energy into electricity. The aim of the study is to evaluate the potential of a mature oil field to generate electricity and predict the evolution of energy potential with time considering the current development plan for the field. This plan was designed to maximize oil production in the field and did not consider possible electricity cogeneration from geothermal energy. The study was conducted in a sector of a mature oilfield including 15 producers currently producing about 10,000 barrels of liquid per day and with a 97% water-cut. A workflow was created to estimate the potential of electricity generation considering current and forecast liquid production rates, the nature of the secondary working fluid used in the Organic Rankine Cycle (ORC) and the minimum ejection temperature limits, defined by the operator, to avoid difficulties in surface separation processes. This paper describes the surface process used for thermal energy to electricity conversion, and presents the workflow used to estimate electricity generated from simulation results considering uncertainty tied to some fluids and rocks parameters.

EOR surfactants are usually formulated at the initial reservoir temperature. Is this a correct approach? Field data from three Single-Well Chemical Tracer pilots in North Africa are used to answer this question. The objectives are, first, to provide a realistic image of the temperature variations inside the water-flooded reservoir; second, to demonstrate the impact of such temperature variations on the surfactant performances; and last, to introduce a new methodology for estimating the target temperature window for surfactant formulations. During pre-SWCTT pilot tests, water injection, shut-in and back-production were performed. The bottom-hole temperature was monitored to evaluate the reservoir temperature changes (initially at 120°C) and to calibrate a thermal model. The thermal parameters were applied to the reservoir model to simulate 30 years of water injection (with its surface temperature varying between 20°C and 60°C) and to obtain a full picture of the temperature variations inside the reservoir. Multi-well surfactant injection was modelled assuming that the surfactant is only efficient within ±10°C around the design temperature. The impact of this assumption on the additional oil recovery was analyzed for several scenarios. The rock thermal transmissivity was found to be the key parameter for properly reproducing the observed data gathered in the North African pre-SWCTT tests. The measured temperature during the back-production phase demonstrated the accuracy of the thermal model parametrization. It proved that the heat exchange between the reservoir and the injected fluid is considerably less than what industry expects: the injected water temperature inside the reservoir remains far below the initial reservoir temperature even after 11 days of shut-in. When simulating various historical bottom-hole injection temperatures and pre-flush durations, the thermal model showed an average cooling radius of 275m, larger than the industry recommended well-spacing for the EOR 5-spot patterns. This was mainly due to the significant temperature difference between the historical injected water and the initial reservoir temperature. Several simulations were performed for 3 representative bottom-hole injection temperatures of 20°C, 40°C and 60°C, varying the surfactant design temperature range between the injection temperature and the initial reservoir temperature. The results showed that regardless of the injection temperature, the simulated additional oil recovery is highest when the design temperature range is close to the injection bottom-hole temperature. This is an important subject since in the EOR industry, the surfactants are usually formulated at the initial reservoir temperature and thus, the impact of the reservoir cooling on the surfactant efficiency is seldom considered. In a water flooded reservoir, the injected chemicals are unlikely to encounter the initial reservoir temperature. This results in a dramatic loss of surfactant performance especially when there is a considerable difference between the initial reservoir and the injected fluid temperatures.

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This paper presents the results of a multi-scenario approach that involves the simulation of chemical EOR processes (polymer- and surfactant-based) for the Ratqa Lower Fars heavy oil (200-1000 cP) field in Kuwait, in order to evaluate the viability of implementing an appropriate chemical EOR strategy. Both technical and economic results are discussed. The approach used involves the simulation of various chemical EOR scenarios (injection of chemical slugs with different durations and concentrations) using several wells patterns (inverted 5-spot, inverted 9-spot, inverted 7-spot with vertical wells, line-drive with horizontal wells) covering various sizes in terms of area. Preliminary simulations of depletion and waterflooding scenarios were also conducted, as base cases to be compared to. Hundreds of EOR scenarios were hence simulated and compared using economic indicators such as the final recovery factor and the cost of chemicals per additional barrel of oil produced, compared to the waterflooding base case scenario. The analysis of the different simulated scenarios shows that due to injectivity issues (low maximum injection pressure to prevent the shale cap rock from being fractured), inverted patterns (inverted 9-spot and especially inverted 7-spot) had to be considered to enhance overall performance and reach promising recovery factors using chemical EOR methods. It is also shown that the impact of the pattern area for the same pattern type (inverted 7-spot configuration) is of paramount importance to the final recovery factor obtained after a fixed simulation duration (20 years in the present case). While the overall efficiency of each EOR process - in terms of recovery factor as a function of the injected solution expressed in pore volume - is kept similar when varying the pattern area, the pattern size is directly linked to the final recovery. Indeed when the pattern area is increased, a smaller volume (in terms of pore volume) of chemical solution can be injected in a fixed timeframe. Finally, the use of simplified economic indicators allowed comparing different EOR processes (polymer and surfactant-polymer) and potential patterns in order to find the most promising configuration in preparation for field implementation. The proposed approach is new as it presents and discusses for the first time the results of a detailed simulation study to evaluate the potential application of chemical EOR processes at the Ratqa Lower Fars heavy oil field in Kuwait. The results of this study are promising and clearly demonstrate the potential applicability of chemical EOR processes in similar heavy oil reservoirs.