From 2009-2011, drilling of several exploration wells in the Topkhana and Kurdamir blocks in southeast Kurdistan, Iraq has delineated a giant oil and gas field with over 4 billion barrels of liquids and over 6 TCF of gas in place. This Oligocene-aged, carbonate-hosted hydrocarbon accumulation is a combination structural and stratigraphic trap. The entire Oligocene succession is composed of interbedded limestone and dolomites with marlstones which were deposited in a carbonate ramp setting. The Oligocene Kirkuk Group is regionally composed of middle ramp foraminiferal and red algae grainstones as well as coral boundstones/rudstones that likely form small bioherms.  Much of the reservoir has good matrix porosity, but low permeability. However, reservoir quality is highly dependent on both the original depositional facies as well as the degree of dolomitization. Predicting the spatial distribution of the best reservoir quality is challenging.

Early diagenesis includes micritization, cementation and compaction. These processes modify the depositional facies, but do not affect the porosity and permeability significantly. Dolomitization is the major diagenetic process that impacts reservoir quality. Oxygen and strontium isotopes suggest reflux dolomitization began near the end of the Oligocene and extended into the earliest Miocene. Full dolomitized facies have the best reservoir quality. Partially dolomitized facies generally have poorer permeability than non-dolomitized facies. Later diagenetic events, anhydrite and calcite cementation, have locally reduced permeability. The late stages of diagenesis are likely associated with the tectonic evolution of the Zagros fold-and-thrust belt. The spatial distribution of the best reservoir quality is dependent on where there is thorough dolomitization or preservation of original depositional porosity and permeability.

Several cores were collected that span the range of depositional environments, diagenetic overprint and reservoir quality. We will present examples of each of these facies as well as supporting material that leads us to our current understanding of the reservoir. Using this base of knowledge, we can continue to interpret the recently collected and processed 3-D seismic data to better predict the spatial distribution of the best reservoir quality rock.

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