A novel methodology has been developed to evaluate low resistivity pay reservoirs in very thin, laminated sand-shale sequences. This technique combines information from both high and low resolution logs to model the petrophysical properties of thin bedded formations. The result is a set of modeled high resolution logs that can be used to yield more accurate estimations of porosity, water saturation and permeability.

A high resolution and a low resolution log response are selected and binned into discrete lithofacies. The average low resolution log responses are statistically calculated for each lithofacies. An initial model is generated by using the high resolution lithology index to select the corresponding low resolution response for each lithofacies, resulting in a set of high resolution logs for each input log. By applying a corresponding vertical response filter to the high resolution log, a synthetic log is created which can be compared to the original. A minimization technique is used to adjust the high resolution responses such that the synthetic and actual logs agree. Since there are an unlimited number of high resolution logs which could result in the same synthetic response, the process is constrained using limits defined for each lithofacies. Evaluation of hydrocarbons in place is then performed on the resulting model.

This paper documents examples in deep-water turbidite reservoirs where thin beds on the scale of a few centimeters were evaluated using this technique. The observations were consistent with core data where this was available. Thin bedded silt and shale laminae had a disproportionate effect on standard resolution measurements due to the abundance of montmorillonite clay which caused elevated neutron and suppressed resistivity responses. The constrained thin-bed analysis yielded considerable enhancement of hydrocarbons in place compared with the evaluation using only standard resolution measurements.

Thin bedded laminated reservoirs occur in many hydrocarbon provinces. The technique described in this paper provides an alternative method for evaluating these formations, helping to reduce reserves uncertainty during a time where accurate reserves evaluation continues to receive high attention.

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