Unlocking Potential in a Thinly Laminated Reservoir by Integrating Electric Logs, Images and Core Analysis: First Case Study in Vietnam

Thin beds are capable of yielding a reasonable amount of hydrocarbon if discovered and evaluated. However, most thin beds are bypassed due to the low vertical resolution of conventional logging tools, which results in significant underestimation of hydrocarbon in the sedimentary unit. To better characterize thin beds and maximize reservoir potential in the thinly bedded reservoirs, a novel methodology has been developed that integrates resistivity images and core data with standard logs.

First, lamination and thin-bed intervals were identified with the help of borehole images and mud logs. Also, high-resolution shallow resistivity from the images was used to output a set of high-resolution logs with a log resolution enhancement technique. This set represents the true layer property and was applied in petrophysical analysis incorporating core study to yield accurate estimations of porosity, water saturation, and permeability. A saturation height function was built from special core analysis (SCAL) to provide an independent saturation estimate for calibrating the petrophysical model. The Thomas-Stieber method, a well-known method for detecting and quantifying laminated sand-shale, was also referenced.

This methodology was applied in the evaluation of five gas wells producing from the same formation. The key well with images, core, and electric logs was used to build the petrophysical and saturation height models. The results show good agreement in estimation of water saturation between independent techniques in the key well and hence demonstrate the value of this technique. The model was propagated to other wells in the same field, and this again showed the validity of the methodology with good agreement in the result between different techniques. The success of the study demonstrates how an integrated thin-bed evaluation model can provide a more definitive representation of thinly bedded sands in terms of their volumes in net sand, sand porosity, and hydrocarbon in place. The methodology yielded considerable improved estimation of hydrocarbons in place compared to the evaluation using only standard resolution measurements. In the thin-bed intervals in the target reservoir, the net thickness increases more than 50% in comparison to the estimation with standard logs.

The improvement in formation evaluation in thin-bed reservoirs resulting from this methodology provides a comprehensive picture of the field reserve that not only helps in the new production plan as input into static and dynamic reservoir models but also leads to effective strategies in field development and management.