Tanjung Field is a brown field which pressure has already depleted and been supported by waterflooding for over a decade. To improve production, surfactant injection, is being studied to be employed in the field. The main objective of this study is to identify parameters that affect oil production increase. History match of the pilot test was carried out to improve the reliability of the reservoir model, hence improving the prediction result of surfactant injection forecast.
History match of the pilot test has been carried out using CMG STARS commercial simulator by considering mechanism inferred from laboratory evaluation such as wettability alteration, surfactant retention, interfacial tension reduction and improvement of mobility control due to lower oil-surfactant emulsion viscosity. These parameters are initially perceived from laboratory result, upscaling and adjustment is applied to field model to further on do sensitivity study. Sensitivity analysis of every parameter is provided to better understand the effect of each mechanism that contributes to the oil incremental result.
Stratigraphically, Tanjung Structure has 7 productive zones: Zone A, B, C, D, E, F and P. Reservoir Zone A has total estimated reserve of 193,732 MMSTB, with recovery factor of 16.3%. The zone consists of conglomerate sandstones with porosity of 21% and permeability ranging from 10 to 100 mD. The field produces light oil within 40 °API, 30% wax content and 1.14 cP of viscosity. T-119 is the well chosen to be injected due to its structural position that ease flow by gravity force to producer wells.
Forecast simulation based on coreflood result has been conducted for pilot test. However, the result was very pessimistic in predicting incremental oil gain and breakthrough time after compared to pilot result. An attempt to history match the surfactant flood pilot is presented by considering phenomena that is not included in the forecast based on additional lab and field data.
Thermal injection methods are usually used for high viscosity oil. The results of previous studies showed that the combination of SF and SFF had the highest increase in oil recovery but still requires further study to determine the optimum strategy. This work is purposed to optimize the development scenario of a combined CSS-SF applied to a heavy oil field located in Sumatera, Indonesia. The recovery factor and NPV become the objective function, and several given and controlled parameters sensitivity toward the objective function are studied. A proxy model based on quadratic multivariate regression is developed to evaluate and get the desired objective function. The reservoir simulation of the thermal recovery process is done using CMG-STARS simulator. The overall workflow of scenario optimization is conducted using CMOST™ module. Optimum development scenario is obtained through maximization of the objective function. This work shows that the combination of proxy model development and optimization results in the best scenario of combined CSS-SF for heavy oil recovery.
Signifi cant portion of CO2 is dissolved in reservoir brine during CO2-Enhanced Oil Recovery. Dissolved CO2 forms an acidic environment which could modify rock-fluid interaction. One of the phenomena that could happen due to this interaction is clay swelling which may affect enhanced oil recovery performance. Several experiments were conducted in a number of sandstone core samples, i.e. Imbibition test, Core flood test, Conductivity test, and pH measurement. Imbibition test was conducted to evaluate CO2-saturated brine (approached with carbonic acid) performance toward oil recovery during five days measurement compared with brine imbibition performance. Moreover, core flood experiment was run to determine the effect of dissolved CO2 in brine on injection in sandstone. This is simulated by injecting brine (base case) followed by carbonic acid under 68.3OC. Thus, conductivity and pH of the imbibed fluids (before after running imbibition test) were measured to justify occurrence of cation exchange. Interpretation of imbibition test indicated that imbibing carbonic acid, at pH value of about four, resulted in loss of oil recovery about 15% compared with brine due to formation damage, caused by clay swelling as sandstone contains clay. The existence of this phenomenon was confirmed by flow resistance at low pH in core sample which was higher than that in brine. This apparent plugging was expected due to severe clay swelling. Meanwhile, the existence of such phenomenon was also clarified with conductivity and pH measurement as there was a great amount of cation exchange. It can be inferred from this study that the rock-fluid interaction from CO2-saturated brine can result in adverse effect, such as injectivity problem and loss of recovery. This finding must be considered in planning CO2 EOR operations, especially when facing condition of watered out oil zone.
Waterflooding is one of the most effective methods to improve oil recovery in mature fields because of its high success ratio, easy in application and cost efficiency. Development until now has shown that Capacitance Resistance Model (CRM) can be used as alternative from reservoir model and simulation studies. CRM can be used as model to predict reservoir characterization and reservoir performance quickly and accurately with only require historical production and injection data. CRM characterizes the reservoir by calculating the connectivity value and the response delay between the injections well and the production well as unknown parameters. Pandhawa Field is a heterogeneous carbonate reservoir with an average permeability of 65 mD with peripheral waterflood since 20 years ago. By knowing the injection efficiency, the optimization process can be carried out by increasing the water injection rate in injection wells that have high efficiency and vice versa. In this study, the performance of waterflood is analyzed using the Capacitance-Resistance Injection-Production Model (CRM-IP) to determine the connectivity of each injection and production well. This study also discuss CRM-IP implementation on MATLAB programming language and optimization of injection rate allocation for the most optimum cumulative oil production. Result of this study indicate total additional oil 505 MBO will be obtained during 120 months period by conduct redistribution water injection management for each injector. By using CRMIP methodology, waterflood management in this field can be done much faster, therefore decision taken for this field will be more effective.
Optimizing water injection rate distribution in waterflooding operations is a vital reservoir management aspect since water injection capacities may be constrained due to geographic location and facility limitations. Traditionally, numerical grid-based reservoir simulation is used for waterflood performance evaluation and prediction. However, the reservoir simulation approach can be time-consuming and expensive with the vast amount of wells data in mature fields.
Capacitance Resistance Model (CRM) has been widely used recently as a data-driven physics-based model for rapid evaluation in waterflood projects. Even though CRM has a smaller computation load than numerical reservoir simulation, large mature fields containing hundreds of wells still pose a challenge for model calibration and optimization. In this study, we propose an alternative solution to improve CRM application in large-scale waterfloods that is particularly suitable for peripheral injection configuration. Our approach attempts to reduce CRM problem size by employing a clustering algorithm to automatically group producer wells with an irregular peripheral pattern. The selection of well groups considers well position and high throughput well (key well). We validate our solution through an application in a mature peripheral waterflood field case in South Sumatra. Based on the case study, we obtained up to 18.2 times increase in computation speed due to parameter reduction, with excellent history match accuracy.
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