QUANTITATIVE PREDICTION OF RESERVOIR QUALITY: A PERMO-CARBONIFEROUS RESERVOIR, SAUDI ARABIA

Quantifying reservoir quality predictions ahead-of-the-bit can reduce exploration risk and add value to field development.

A research project at Saudi Aramco was initiated to assess a new workflow to quantitatively predict reservoir quality. The major technology advance employed here is integration of forward stratigraphic modeling (FSM) and diagenetic modeling. The reservoir chosen for application is a Permo-Carboniferous reservoir in Central Arabia.

The reservoir interval of interest was deposited above the Hercynian Unconformity over a period of 56 Ma. during the upper Carboniferous to lower Permian in central and eastern Saudi Arabia. This Group consists of a succession of sandstones and siltstones that reflects changing climatic and environmental conditions.

FSM has been used as a tool to predict initial reservoir quality in this suite of rocks without direct use of well data. Main inputs are parameters that control the processes that erode, transport, and deposit sediments.

The lowermost sediments of the reservoir were modeled as the products of fluvial depositional systems associated with repeated glacial advances and retreats. Glacial collapse that followed produced large scale lacustrine systems in which deposition of the middle part of this Permo-Carboniferous group took place.

The upper part of the reservoir was modeled as an eolian sedimentary system with episodes of fluvial activity. To our knowledge, this is the first use of process-based technique in the oil and gas industry to model eolian deposits.

Results from the individual models of the reservoir were compared to well and seismic data from the modeled area. Overall, model results correllate well with actually observed sedimentary facies and initial reservoir quality in cores and logs. In addition, stratal geometries seen in the model matched seismically defined geometries very well. Compacted thicknesses at well locations were in very close agreement with those observed in well logs.

A small pilot study incorporating diagenetic effects was completed recently. The results from this study are very encouraging to proceed with the workflow.