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In the face of the escalating global energy demand, the challenge lies in enhancing the extraction of oil from low-pressure underground reservoirs. The conventional artificial gas lift method is constrained by the limited availability of high-pressure gas for injection, which is essential for reducing hydrostatic bottom hole pressure and facilitating fluid transfer to the surface. This study proposes a novel ‘smart gas’ concept, which involves injecting a gas mixture with an optimized fraction of CO2 and N2 into each well. The research introduces a dual optimization strategy that not only determines the optimal gas composition but also allocates the limited available gas among wells to achieve multiple objectives. An extensive optimization process was conducted to identify the optimal gas injection rate for each well, considering the limited gas supply. The study examined the impact of reducing available gas from 20 to 10 MMSCFD and the implications of water production restrictions on oil recovery. The introduction of smart gas resulted in a 3.1% increase in overall oil production compared to using natural gas. The optimization of smart gas allocation proved effective in mitigating the decline in oil production, with a 25% reduction in gas supply leading to only a 10% decrease in oil output, and a 33% reduction resulting in a 26.8% decrease. The study demonstrates that the smart gas approach can significantly enhance oil production efficiency in low-pressure reservoirs, even with a substantial reduction in gas supply. It also shows that imposing water production limits has a minimal impact on oil production, highlighting the potential of smart gas in achieving environmentally sustainable oil extraction. Furthermore, the implementation of the smart gas approach aligns with global environmental goals by potentially reducing greenhouse gas emissions, thereby contributing to the broader objective of environmental sustainability in the energy sector.
In the face of the escalating global energy demand, the challenge lies in enhancing the extraction of oil from low-pressure underground reservoirs. The conventional artificial gas lift method is constrained by the limited availability of high-pressure gas for injection, which is essential for reducing hydrostatic bottom hole pressure and facilitating fluid transfer to the surface. This study proposes a novel ‘smart gas’ concept, which involves injecting a gas mixture with an optimized fraction of CO2 and N2 into each well. The research introduces a dual optimization strategy that not only determines the optimal gas composition but also allocates the limited available gas among wells to achieve multiple objectives. An extensive optimization process was conducted to identify the optimal gas injection rate for each well, considering the limited gas supply. The study examined the impact of reducing available gas from 20 to 10 MMSCFD and the implications of water production restrictions on oil recovery. The introduction of smart gas resulted in a 3.1% increase in overall oil production compared to using natural gas. The optimization of smart gas allocation proved effective in mitigating the decline in oil production, with a 25% reduction in gas supply leading to only a 10% decrease in oil output, and a 33% reduction resulting in a 26.8% decrease. The study demonstrates that the smart gas approach can significantly enhance oil production efficiency in low-pressure reservoirs, even with a substantial reduction in gas supply. It also shows that imposing water production limits has a minimal impact on oil production, highlighting the potential of smart gas in achieving environmentally sustainable oil extraction. Furthermore, the implementation of the smart gas approach aligns with global environmental goals by potentially reducing greenhouse gas emissions, thereby contributing to the broader objective of environmental sustainability in the energy sector.
As oil and gas development in Indonesia is shifting towards offshore environment, automation is essential for reducing operating cost. PHE ONWJ as the biggest oil and gas operator in Indonesia develops an automated field operation for gas lift optimization, called PiNTAR. PHE ONWJ has been operating gas lift wells for almost 40 years. The biggest challenge is how to efficiently conduct the business operations in offshore environment. The current regular operations (for instance production monitoring) are conducted manually in monthly basis. It is time-consuming and requires long time for trouble shooting. PiNTAR is designed by PHE ONWJ by integrating smart signal system that can be operated remotely without having to be physically presence at the site. The system is integrated with SCADA sensors, satellite system and fully electronic transmitter that sends production data and related parameters to PHE ONWJ head office to be analyzed 24/7 and mitigated if necessary. PiNTAR has been implemented on more than 50 wells in PHE ONWJ working areas. PHE ONWJ also provides interactive Graphical User Interface based software for monitoring and production adjustment purposes. Standardization is also performed therefore PiNTAR can be implemented in a wider area, with different gas lift situations. PiNTAR enables operators to quickly diagnose flow irregularities ranging from adjusting injected Gas Liquid Ratio (GLR) to minimize annular flow, modify choke openings, dynamic reallocation of injected gas from multiple well systems, and also allows the team to comprehend a significant amount of flow characteristics in gas lifted wells as measurements are taken in a very small-time frame, ranging from minutes to seconds. PiNTAR also enables automated production test that enables the construction of real time Gas Lift Performance Curve, which reduces operator workload and enables dynamic gas lift optimization. Implementation of PiNTAR also reduces HSSE risks for rope jumping operations in offshore and increases efficiency of fuel and personnel timing in platform. The publication presents a success story of gas lift automated optimization using in-house development from PHE ONWJ called PiNTAR. Significant monetary efficiency as well as production increase has been observed during the implementation, encouraging the company to pursue further field automation efforts.
The QQ Field in the Gulf of Suez is a mature, geologically complex with multiple stacked, faulted reservoirs, with commingled production between different reservoirs. This paper illustrates the power of an automated tool to perform systematic, rapid, and detailed assessment of the reservoir performance, identify the key recovery obstacles and prepare remedial plans to enable the reservoir to produce to its full potential. The well and reservoir data were processed to compute a series of metrics and key performance indicators at various levels (well, layer, reservoir, well groups, etc.). The tool has several automated modules to facilitate rapid, metric-driven reservoir assurance and management. These modules include: (i) well production/injection allocation, (ii) wells decline curve analysis including event-detection, (iii) pressure and voidage analysis, and (iv) Contact analysis. Using performance analytics, the study quickly identified ways to improve the health of the reservoir and maximize its value. The QQ Field predominantly produces from two formations: Nubia and Nezzazat. Furthermore, there are multiple sub-layers in each formation. Reliable flow unit allocation is critical to gauge contribution of each layer, identify the undrained areas of the reservoir, and locate future development opportunities. The flow unit allocation module incorporates all available data such as PLT/ILT data, completion history, permeability of each flow unit at well level, relative pressures, and water influx model. Based on the allocated production, the current recovery factors in Nubia and Nezzazat are approximately 60% and 20% respectively. Analysis of RFT data reveals good vertical communication across Nubia. However, in some areas there is clear pressure discontinuity across layers. The reservoir pressure has dropped below the bubble point in both formations. As a result, water injection was initiated. The pressure in all parts of Nubia was restored above bubble point. Aquifer influx is sufficient to support the current withdrawal rates and further water injection is unnecessary. However, Nezzazat has a significantly higher reservoir complexity and therefore, shows a large variation in pressure behavior. It needs water injection to maintain the reservoir pressure above the bubble point in all parts of the reservoir. Based on the flow-unit allocation, the voidage replacement ratio (VRR) was calculated for each area and each layer. Even though the overall VRR in the waterflooded areas is above one, the distribution of the injected water is uneven. Redistributing injected water and ensuring that all the areas and all the layers are adequately supported will help to maximize recovery. The prolonged dip in oil price demands extreme efficiency. Sound reservoir management must not require unreasonable time or manpower. The rapid, automated analysis enables quick identification of the key areas for improvement in reservoir management practices and maximize the value of the asset.
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