scholarly journals OIL RESERVOIR CHARACTERIZATION AND CO2 INJECTION MONITORING IN THE PERMIAN BASIN WITH CROSSWELL ELECTROMAGNETIC IMAGING

2004 ◽  
Author(s):  
Michael Wilt
2021 ◽  
Author(s):  
Mohamad Yousef Alklih ◽  
Andi Ahmad Salahuddin ◽  
Karem Alejandra Khan ◽  
Nidhal Mohamed Aljneibi ◽  
Coriolan Rat ◽  
...  

Abstract 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.


2011 ◽  
Author(s):  
Valerio Parasiliti Parracello ◽  
Martin Bartosek ◽  
Michela De Simoni ◽  
Carolina Mallardo

2009 ◽  
Vol 28 (7) ◽  
pp. 856-860 ◽  
Author(s):  
Fereidoon Vasheghani ◽  
Larry R. Lines

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