Determination of reservoir wettability based on resistivity index prediction from core and log data
| Autor: | Kegang Ling, Jungui Feng, Zhiqiang Mao, Ziyan Feng, Yuntao Zhong, Cheng Feng |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Capillary pressure
Materials science Petrophysics Soil science 02 engineering and technology 010502 geochemistry & geophysics Geotechnical Engineering and Engineering Geology 01 natural sciences Core (optical fiber) Fuel Technology 020401 chemical engineering Reservoir modeling Formation evaluation Wetting 0204 chemical engineering Geometric mean Porosity 0105 earth and related environmental sciences |
| Zdroj: | Journal of Petroleum Science and Engineering. 205:108842 |
| ISSN: | 0920-4105 |
| DOI: | 10.1016/j.petrol.2021.108842 |
| Popis: | With the increasing demand of precisive reservoir characterization in exploration and development of oil and gas, wettability plays a more and more significant role because it influences oil and water distribution. The determination of wettability has been a challenge to the researchers focusing on this area. In this study, a new method is proposed for the determination of wettability based on resistivity index prediction. Firstly, the model for estimating resistivity index using capillary pressure, porosity and median pressure by J-function is derived. Secondly, the model to estimate resistivity index via T2 time, porosity and T2 geometric mean is derived, which combines J-function with Schlumberger-Doll-Research (SDR) model. Thirdly, a new parameter, the ratio of mean saturation index calculated from first method to the one calculated from second method, is used to determine the reservoir wettability. To calibrate and verify the established models, 30 cores were acquired for the petrophysical experiments. The experimental results of 25 cores are used to calibrate the established models and build the quantitative relationship between the wettability and the ratio of mean saturation index, with a relevance of 0.96. Besides, the calibrated model is tested by using the experiment data of the rest 5 cores. The estimated wettability conforms to the experimental results. Finally, the processing and interpreting results of log data also indicate that the proposed model for quantitative prediction of wettability features good application effect. In conclusion, the proposed method for quantitative prediction of wettability is effective and highly reliable, which solves a difficult problem in formation evaluation. |
| Databáze: | OpenAIRE |
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