Evening Talk

Evening Talk - "A Systematic Approach to Evaluate Hydrocarbons in Thinly bedded reservoirs"

Q. R. Passey, K. E. Dahlberg, K. B. Sullivan, H. Yin, Y.H. Xiao, A. G. Guzman-Garcia3, R. A Brackett, K.Shmyglya

Monday 21st July, 6pm at Geological Society, Piccadilly, London.

ABSTRACT

Many oil and gas reservoirs contain significant volumes of recoverable hydrocarbons in intervals where the average bed thickness is below the resolution of conventional logging tools. The presence of thin beds increases the uncertainty in all approaches to hydrocarbon pore thickness estimates. Standard cutoff methods cannot be used to determine net pay reliably for thinly bedded intervals.

The presence of thin shales has a disproportionate effect on resistivity log measurements, reducing their sensitivity to the presence of hydrocarbons. Conventional log-analysis methods, including classical shaly sand methods, typically underestimate hydrocarbon volumes in such thinly bedded intervals, often by 30% or more. A further complication induced by thin bedding is macroscopic anisotropy, which causes resistivity logs to measure different average values depending on the relative angle between the borehole and bedding planes.

In ExxonMobil, a two-pronged approach has been developed to improve the evaluation of in-place hydrocarbons in thinly bedded reservoirs:

1. For intervals where the average bed thickness is greater than about one foot, a high-resolution measurement, such as an image log, is used to define individual bed boundaries and construct a detailed earth model. Using the high-resolution earth model, detailed 1-D and 2-D forward models are generated for resistivity logging tools and simplified 1-D models are produced for porosity and lithology logs. Modeled responses are compared to measured log responses, and the earth model is adjusted until a match between the modeled and measured logs is obtained.
   
   
   
2. For reservoir intervals where the average bed thickness is below one foot, a unique low-resolution approach is used without attempting to resolve individual beds. Here, a statistical earth model for the entire thinly bedded interval is formulated. This model comprises two or more bed types and assumptions about the petrophysical properties and relative frequencies of each type. Mathematical models then predict the averaged log responses over the interval, accounting for the effects of thin bedding and macroscopic anisotropy. A Monte Carlo inversion method is used to find the ranges of bed properties and frequencies that yield matches between the predicted and measured log averages, thus, resulting in an improved estimate of in-place hydrocarbons, including an estimate of the uncertainty.

This systematic, two-pronged approach has been used in reservoir evaluations worldwide and has resulted in improved, and often significantly increased, estimates of in-place hydrocarbons in thinly bedded reservoir intervals. The result of either interpretation can be compared to that derived from NMR analysis when these logs have been acquired in the well of interest.