Abstract
Organically rich mud rocks are currently targeted for unconventional oil and gas exploration and development in many places around the world, including Saudi Arabia. The Jurassic Tuwaiq Mountain Formation in the Jafurah basin, located east of the giant Ghawar oil field is the primary focus of this paper. The formation has been divided into 3 Tiers possessing varying reservoir qualities. Of these Tiers, the bottom Tier 1 possesses the most excellent shale gas characteristics such as high total organic content (TOC), low clay content and high hydrocarbon saturation. The formation of interest is also in the proper maturity window for hydrocarbon generation and relatively shallow, making it attractive for an economic unconventional shale gas play. To expedite shale gas development in Saudi Arabia, a phased de-risking strategy has been implemented. The strategy consists of four phases; exploration, appraisal, pilot and development. Three wells, representing the first unconventional reservoir exploration wells drilled in the Jafurah basin have been selected for this study. The wells were drilled vertically, cored and logged. Wells were then sidetracked with 5000 ft horizontal laterals and stimulated through multistage hydraulic fracturing. All stimulated wells flowed gas and condensate to surface. This paper summarizes, with examples, a workflow for characterizing the Tuwaiq Mountain Formation as a potential unconventional liquid rich gas play. Crucial to this, is the development of a reservoir quality predictive model for acreage grading, sweet spot identification and fracturing stage selection. This methodical approach is applicable to the evaluation of any emerging unconventional play.
•The Jafurah basin in Saudi Arabia possesses excellent shale gas attributes.•The basin spreads over a large area equivalent in size to the Eagle Ford play.•A phased de-risking strategy is being implemented to explore this frontier basin.•Targeted zones exhibit high TOC/hydrocarbon saturation, and low clay content.•A reservoir quality prediction model was developed for sweet spot identification.