This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.
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Abstract
Estimating pre-drill volumes in hydrocarbon exploration involves dealing with geological and technical uncertainties. The prediction of the hydrocarbon column height is widely recognized as the primary driver of uncertainty in volumetric estimates. The oil and gas industry continues to renew efforts to limit such uncertainties because of the potential economic costs of inaccurate estimation, yet estimation of pre-drill volumes remains an in-exact science. This study introduces new empirical data from the Norwegian Continental Shelf, and aims to improve accuracy in hydrocarbon column height prediction. We use column height, trap height and burial depth data to calculate the degree of hydrocarbon trap fill for each of the 242 studied discovery wells. The data is aggregated into a simple forward probability model to calculate the probability of encountering different ranges of trap-fill, based on burial depth and trap height. The distribution of trap-fill ratios clearly correlates with both trap height and burial depth, thus indicating that the same pre-drill column height distribution should not be used for all prospects. These findings strongly suggest that the prospect’s dimensions and burial depth are used alongside other technical subsurface factors to determine the most suitable pre-drill hydrocarbon column height distribution. This method contributes to reducing the largest source of uncertainty, which in turn reduces the overall uncertainty associated with pre-drill volume estimation. Such an approach will increase the accuracy of pre-drill volume estimation, leading to more appropriate future development plans. We recommend that the presented methods and lessons learnt are applied in basins settings worldwide.
DOI
https://doi.org/10.31223/osf.io/zsakb
Subjects
Analysis, Earth Sciences, Geology, Mathematics, Physical Sciences and Mathematics
Keywords
uncertainty analysis, Base-rate data, Burial depth, Norwegian Continental Shelf, Probability distribution, Prospect analysis, Trap height
Dates
Published: 2019-10-03 08:03
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