<em>Steamflood is the most successful thermal EOR applied throughout the world and have produced the biggest portion of oil from EOR methods. As high intensity energy and associated cost are put to produce oil, optimization in any level can have tremendous impacts. Optimization in steamflood operation can be achieved by optimizing steam injection (rate, time), especially in mature pattern/ field or nearing the end of field life/ abandonment. This objective can be done thru utilization of retained heat in the reservoir and overburden/ underburden as they are not instantaneously produced with fluids. By using reservoir simulation, it can be shown that injection is not necessary to be continue until abandonment but can be stopped at a much earlier time hence a much profitable steamflood operation can be achieved.</em>
COVID-19's pandemic condition affects various industries, including energy and the upstream industry. One of the many negative consequences of this circumstance is that it forces the organization to come up with new strategies to cut employee number while maintaining full site operations. Many service and oil firms have successfully implemented operations wells around the world, improving not just wellsite efficiency but also cost optimization and safety. During the implementation, it is observed that remote operations are good solution even though it is challenging. This paper describes the development of remote operations in the oil and gas industry and also recommendations regarding the implementation process hopefully can add more value to Oil and Gas Industries for the future while facing difficult situation. Lastly Opportunities and Threats analysis is done to conclude how remote operations will help operators to add more value to operations.
In addition to extensive information that has been obtained from pre-feasibility, exploration, and drilling phase, we can improve our knowledge of reservoir behavior related to thermal extraction using sensitivity analysis. Such analysis is commonly applied to address technical uncertainty and risks in economic evaluation. The purpose of this study is to determine the parameters that have the most influence on thermal power generation using two different approaches named one-factor-at-a-time or OFAT and response surface method or RSM. Moreover, RSM analysis allowed us to make a predictive model for thermal power extracted in liquid-dominated geothermal reservoir. Literature study is conducted to understand various properties commonly encountered in a liquid-dominated geothermal reservoir including porosity, conductivity, reservoir temperature, and permeability. This information is then used to construct reservoir model in CMG STARS simulator with a single producer and injector. Two different sampling method, named OFAT and Box-Behnken are used to construct dataset, each contains different combination of levels of reservoir porosity, conductivity, temperature, permeability, and re-injection temperature. A total of 31 models using OFAT method with 7-level for each parameter are simulated to understand individual effect of each parameter. Meanwhile, 47 models are constructed using RSM method with 3-level for each parameter to evaluate the effect of interaction between parameters on thermal generation potential as well as constructing predictive model. Sensitivity analysis using both OFAT and RSM agree that the reservoir temperature is the most significant characteristic of geothermal reservoir to affect its thermal power potential. Meanwhile, re-injection temperature that initially expected to strongly effect the lifetime and sustainability of a liquid-dominated geothermal utilization is insignificant. This finding suggest that optimization re-injection temperature is solely for the purpose of maintaining sustainability of geothermal reservoir or cater the concern of environmental issue on wastewater management, and not for maximizing the thermal extraction.
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