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This paper presents an integrated subsurface study that focuses on delivering field development planning of two reservoirs via comprehensive reservoir characterization workflows. The upper gas reservoir and lower oil reservoir are in communication across a major fault in the crest area of the structure. Gas from the upper reservoir, which is not under development, is being produced along with some oil producers from the oil reservoir as per acquired surveillance data. Pressure depletion is observed in observer wells of the upper reservoir, which substantiate both reservoirs communication. The oil reservoir is on production since 1994, under miscible hydrocarbon water alternating gas injection (HCWAG) and carbon dioxide (CO2) injection. The currently implemented development plan has been facing several complexities and challenges including, but not limited to, maintaining miscibility conditions, sustainability of production and injection in view of reservoirs communication, reservoir modeling challenges, suitability of monitoring strategy, associated operating costs and expansion of field development in newly appraised areas. In this study, an assessment of multiple alternative field development scenarios was conducted; with an aim to tackle field management and reservoir challenges. It commenced by a comprehensive synthesis of seismic, petrophysical (including extensive core characterizations), geological, production and reservoir engineering data to ensure data adequacy and effectiveness for development planning. The process was followed by evaluation of the historical reservoir management, HCWAG and CO2 injection practices using advanced analytics to identify areas for improvement and accelerate decision making process. The identified areas of improvement were incorporated into a dynamic model via diverse set of field management logics to screen wide range of scenarios. In the final step, the optimal scenarios were selected, in line of having strong economic indicators, honoring operational constraints, corporate business plan and strategic objectives. The comprehensive and flexible field management logic was set up to target different challenges and was used to extensively screen hundreds of different field development scenarios varying several parameters. Examples of such parameters are WAG ratio, injection pressures for both water/gas and CO2, cycle duration, well placement, reservoir production and injection guidelines, different co-development production schemes coupled with static and dynamic uncertainty properties against incremental oil production and discounted cash flow. The simulation results were analyzed using standardized approach where a number of key indicators was cross-referenced to produce optimal field development scenarios with regards to co-development effect of both reservoirs, miscibility conditions, balanced pressure depletion, harmonized sweep as well as robust discounted cash flow. Strong management support, multi-disciplinary data integration, agility of decision making and revisions in a controlled timeframe are considered as the key pillars for success of this study. The adopted workflow covers subsurface modeling aspects from A-Z and following reservoir characterization and modeling best practices. The methodology applied in this study uses an integrated subsurface structured approach to tackle reservoirs challenges and co-development, generate alternative development options leveraging on data analytics techniques and advanced field management strategies.
This paper presents an integrated subsurface study that focuses on delivering field development planning of two reservoirs via comprehensive reservoir characterization workflows. The upper gas reservoir and lower oil reservoir are in communication across a major fault in the crest area of the structure. Gas from the upper reservoir, which is not under development, is being produced along with some oil producers from the oil reservoir as per acquired surveillance data. Pressure depletion is observed in observer wells of the upper reservoir, which substantiate both reservoirs communication. The oil reservoir is on production since 1994, under miscible hydrocarbon water alternating gas injection (HCWAG) and carbon dioxide (CO2) injection. The currently implemented development plan has been facing several complexities and challenges including, but not limited to, maintaining miscibility conditions, sustainability of production and injection in view of reservoirs communication, reservoir modeling challenges, suitability of monitoring strategy, associated operating costs and expansion of field development in newly appraised areas. In this study, an assessment of multiple alternative field development scenarios was conducted; with an aim to tackle field management and reservoir challenges. It commenced by a comprehensive synthesis of seismic, petrophysical (including extensive core characterizations), geological, production and reservoir engineering data to ensure data adequacy and effectiveness for development planning. The process was followed by evaluation of the historical reservoir management, HCWAG and CO2 injection practices using advanced analytics to identify areas for improvement and accelerate decision making process. The identified areas of improvement were incorporated into a dynamic model via diverse set of field management logics to screen wide range of scenarios. In the final step, the optimal scenarios were selected, in line of having strong economic indicators, honoring operational constraints, corporate business plan and strategic objectives. The comprehensive and flexible field management logic was set up to target different challenges and was used to extensively screen hundreds of different field development scenarios varying several parameters. Examples of such parameters are WAG ratio, injection pressures for both water/gas and CO2, cycle duration, well placement, reservoir production and injection guidelines, different co-development production schemes coupled with static and dynamic uncertainty properties against incremental oil production and discounted cash flow. The simulation results were analyzed using standardized approach where a number of key indicators was cross-referenced to produce optimal field development scenarios with regards to co-development effect of both reservoirs, miscibility conditions, balanced pressure depletion, harmonized sweep as well as robust discounted cash flow. Strong management support, multi-disciplinary data integration, agility of decision making and revisions in a controlled timeframe are considered as the key pillars for success of this study. The adopted workflow covers subsurface modeling aspects from A-Z and following reservoir characterization and modeling best practices. The methodology applied in this study uses an integrated subsurface structured approach to tackle reservoirs challenges and co-development, generate alternative development options leveraging on data analytics techniques and advanced field management strategies.
Conventional gas lift optimization methods in reservoir simulation prioritize naturally flowing wells over wells requiring gas lift to meet production mandates. However, maximizing the value of gas lift wells may unlock significant untapped reserves. This paper presents the application of a Smart Gas Lift Optimization (SGLO) workflow on a complex giant onshore carbonate oilfield to maximize production and recovery through an efficient gas lift optimization method. The Smart Gas Lift Optimization consists in restructuring the well group hierarchy to define parallel structures for naturally flowing wells and gas lift wells to enable existing wells with gas lift to be produced with a higher priority, hence maximizing their production potential using gas lift optimization. Wells meeting certain conditions defined on production, gas-oil ratio, water cut, or pressure would be automatically assigned to the different entities of the gas lift group structure to maximize their production and enable the gas lift optimization mechanism to obtain the most optimal gas lift rate under the constraints specified. The workflow was applied on a giant onshore carbonate oilfield with a complex structure and a very high well count through an automated tool that was developed for setting up the full SGLO workflow by automatically parsing reservoir simulation model input files and define the required group structure, along with all necessary settings for gas lift optimization and SGLO. Results between the non SGLO case and the SGLO case were compared to assess the difference in production between these two scenarios. The SGLO case provided a substantial boost to the total oil production compared to the non SGLO case and the duration of the production plateau target was extended further. The gas lift optimization allocation is effectively allocating gas lift even if the production plateau is already reached and proposing a gas lift rate allocation that maintains the existing gas lift wells alive and improves the total reservoir recovery while reducing by-passed oil in place. The allocation prioritized to gas lift wells significantly increases the value of the existing gas lift wells that are pushed to their largest potential, reducing requirements for infill drilling. Although the Smart Gas Lift Optimization uses all the principles of regular gas lift optimization combined to an additional logic that triggers the gas lift wells to produce with an optimum gas lift rate based on an economic gradient defined. The tool was fully automated to apply the SGLO workflow in a matter of minutes even for a highly complex reservoir model.
The traditional optimum modes of gas-lift production are usually established by taking the injected gas rate as a decision variable and maximum oil production as the objective function. After solving the model, the injected gas rates of single wells are obtained, and then the oil productions of single wells, the total oil productions of well groups and economic profit can be obtained. However, the models do not take both different types of gas-lift performance curves (GLPCs) and the cost factors of gas-lift production technique into account. On the basis of GLPCs, this paper introduces the factors of a gas-lift production technique, which includes the water cut of crude oil, cost of gas injection and water treatment, and oil and gas prices. The concept of a gas-lift economic performance curve (GLEPC) is proposed, and an optimum gas allocation model is established, considering different types of GLPCs and taking economic benefits as the objective, and the model is solved by the method of mixed penalty function. Taking gas-lift well group JD as an example, four gas-lift gas allocation schemes are obtained, and the proposed economical optimum model is applied to optimize gas allocation and analyze profit. What is more, the oil production rate and the result of optimum gas allocation taking maximum oil production rate as the objective in the model are calculated and compared. Then the gas allocation scheme with maximum economical profit is selected, and the significance of considering different types of GLPCs and taking economic benefits as the objective to gas allocation is confirmed.
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