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Simplified and More Accurate Clay Typing Enhances the Value Added by Petrophysical Evaluation of Shale Plays and Tight Gas Sand Reservoirs

Chitale, Vivek D.1
1 Halliburton, Houston, TX.

The paper addresses the importance of correct and meaningful application of knowledge available from clay science research to the petrophysical formation evaluation of shales and shaly sand reservoirs to assess reservoir quality and compute fluid bulk volumes. It underscores the need to establish clay mineral types when performing petrophysical formation evaluation of shaly sand reservoirs. As shown, accuracy in clay typing is based primarily on using correct log response values for pure clay types such as smectite. The paper discusses modifications necessary to prevalent data on such log responses, based on previous clay characterization work. Simplified clay typing based on triple combo conventional logs is then possible using the rationalized values for nuclear logs. Using examples to validate these concepts, the paper highlights that clay mineral composition of a subsurface formation controls nuclear log responses -which are bulk measurements - regardless of mode of distribution of constituent clays and whether they are digenetic or depositional.

Most common models for shaly sand reservoirs correct for clay bound water in shaly rocks, typically basing the “correction” on computed volume of clay or shale from logs, or from a laboratory-derived weight fraction of clay size particles in rocks (<4 microns). Now, considering that clay bound water (CBW) represents water of adsorption bound to the surface of a given clay mineral, the “correction” should be done only if the rock actually contains a clay mineral characterized by sufficient quantity of CBW to affect the logs that need correction! As noted, smectite is the only clay type characterized by any significant amount of CBW; clearly, knowing clay type is essential before selecting a formation evaluation model.

Implications of accurate clay typing for shale plays and tight gas sands is obvious in terms of achieving greater accuracy in predicting reservoir quality, calculating reserves, and reservoir modeling, thus helping reduce overall E&P risk.


AAPG Search and Discovery Article #90090©2009 AAPG Annual Convention and Exhibition, Denver, Colorado, June 7-10, 2009