Global experience in cold Gas Oil Gravity Drainage (cGOGD) recovery with crestal gas injection of infield produced gas is very limited, but is a proven economic recovery method for fractured carbonate reservoirs in North Oman. Despite decades of research in nature of fluid flow in fracture-matrix media and application of sophisticated tools in building fracture model of a naturally fractured reservoir (NFR) reliable prediction of the GOGD production performance often proved elusive. Characterization of fracture networks and modeling of matrix-fracture transfer function, gravity induced fluid flow in heterogeneous matrix media especially in case of capillary discontinuity due to tight interbedded matrix and capillary pressure hysteresis are the key challenges for reservoir modeller. Re-infiltration of oil into lower matrix blocks, matrix permeability, fracture density and spacing, wettability and reservoir fluid properties have significant impact on the well and field performance. The risk posed due to undermining the key modeling parameters have huge implication on facility design, subsurface concept and value of the project. The challenges in upscaling the fracture properties in a range of grid scale, experimental design for history matching and uncertainty analysis, understanding the oil rim development in leached zone and numerical options are some of the key aspects which have been illustrated in this paper. The field being on primary production since 1985, showed poor recovery and high water cut. Multi-episodic tectonic events resulted in variable fracture intensity and fracture permeability anisotropy. This study investigated the effects of the parameters on cGOGD recovery process, operating strategy (e.g., gas injection rate and liquid offtake) and on the overall field performance. The development decisions are not simply relied upon the dynamic simulator results, but an integrated understanding from comprehensive analytical calculations for multiple recovery mechanism such as fluid expansion, fracture oil displacement, gravity drainage from background matrix and leached zone and analogue field GOGD performance were taken into consideration. The subsurface development decisions such as producer location with respect to faults and lineament, well pattern & spacing, producer depth, gas injector locations, gas injection scenarios, aquifer pump-out wells and maximum off-take rate were analyzed and optimum decision could be taken from multi-scenario modeling studies. The GOGD development could increase the field recovery up to ~9% at low UTC and positive NPV. A pragmatic and integrated modeling workflow with multi-scenario modeling approach was pursued to address the development risk which facilitated the field to be economically developed. The key modeling challenges have been highlighted for GOGD modeling process with gas recycling option of development which can be replicated in similar fields in PDO.

In recent years, with the steep drop and increased volatility in oil price, there is an urgency for making our field (re-development) plans more dynamic and efficient with faster payback and with particular emphasis on robustness against uncertainties. This paper describes a root cause analysis and a methodology to achieve up to ~30% improvement in field development planning project cycle and developing a better-integrated reservoir understanding. A comprehensive integrated analysis of available data is a key success criterion for robust decision-making. A detailed value stream mapping and a timeline analysis for data analysis in the hydrocarbon maturation process revealed that our process cycle efficiency is only 16% with a significant room for improvement. Any improvement can be directly translated to man-hour cost saving and acceleration of oil delivery. Effective use of technology and digitalization for knowledge management, standardized ways of working and easy access to historical data, analysis and diagnostics were identified as key focus areas to improve delivery. An innovative process and web based digital platform, iResDAT, is developed for accelerating data analysis. It mines from volumes of petro-technical databases and translates data into standardized diagnostics using latest data analytics and visualization technologies. It has already reduced dramatically the time to mine critical subsurface data and prepare required integrated diagnostics that are auditable and can be re-created in a few seconds. Based on the early pilot studies the cycle time reduction in the data analysis phase is close to 30% with improved quality and standardization of the integrated analysis. It has already transformed the ways of working where the subsurface discussion can happen across disciplines using a single platform that enforces early integration for reservoir understanding and associated uncertainty characterization. It is a web-based platform where the diagnostic dashboards are crowd sourced; sustained and enhanced by the business to ensure the relevance and sustainability with the Corporate Data Management and IT functions. It is a building block towards quality controlled and auditable data analysis and interpreted dataset, which may form the backbone for any advanced analytics in future to enable digitally enabled hydrocarbon maturation.