Efficient True Resistivity Prediction and Time Optimization in PcRI Measurements: A Results-Driven Approach
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| Format: | Recurso digital |
| Langue: | anglais |
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2025
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| _version_ | 1866902058169270272 |
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| author | Nourani, Meysam Munoz Beltran, Alvaro Pruno, Stefano Rodvelt, Hans-Erik |
| author_facet | Nourani, Meysam Munoz Beltran, Alvaro Pruno, Stefano Rodvelt, Hans-Erik |
| contents | <p><span>This study aims to validate models developed for predicting true resistivity and water saturation in<br>drainage capillary pressure and formation resistivity index (PcRI) measurements using porous plate methodology.<br>The true resistivity model enables the calculation of the time required to reach equilibrium for these key parameters.<br>To validate the petrophysical resistivity model, an extensive database was used, comprising over 12,500 data points<br>collected from sandstone and carbonate rocks analysed under various fluid systems, including crude oil/water,<br>laboratory oil/water, and gas/water. The true resistivity and water production models reliably estimated true<br>resistivity and water saturation as a function of time for both rock types. Based on transient drainage PcRI data, the<br>models can predict equilibrium true resistivity and water production, significantly reducing measurement time and<br>accelerating PcRI measurements by up to 63% in some cases. This optimization improves analysis timing and<br>facilitates data interpretation, making the models as an important tool for enhancing efficiency in laboratory PcRI<br>analysis. These models also have practical applications in monitoring and controlling the quality of transient<br>drainage PcRI data. Additionally, they support the interpretation and validation of results, ensuring a more reliable<br>and robust petrophysical evaluation.</span> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16814401 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Efficient True Resistivity Prediction and Time Optimization in PcRI Measurements: A Results-Driven Approach Nourani, Meysam Munoz Beltran, Alvaro Pruno, Stefano Rodvelt, Hans-Erik 2025 SCA Poster <p><span>This study aims to validate models developed for predicting true resistivity and water saturation in<br>drainage capillary pressure and formation resistivity index (PcRI) measurements using porous plate methodology.<br>The true resistivity model enables the calculation of the time required to reach equilibrium for these key parameters.<br>To validate the petrophysical resistivity model, an extensive database was used, comprising over 12,500 data points<br>collected from sandstone and carbonate rocks analysed under various fluid systems, including crude oil/water,<br>laboratory oil/water, and gas/water. The true resistivity and water production models reliably estimated true<br>resistivity and water saturation as a function of time for both rock types. Based on transient drainage PcRI data, the<br>models can predict equilibrium true resistivity and water production, significantly reducing measurement time and<br>accelerating PcRI measurements by up to 63% in some cases. This optimization improves analysis timing and<br>facilitates data interpretation, making the models as an important tool for enhancing efficiency in laboratory PcRI<br>analysis. These models also have practical applications in monitoring and controlling the quality of transient<br>drainage PcRI data. Additionally, they support the interpretation and validation of results, ensuring a more reliable<br>and robust petrophysical evaluation.</span> </p> |
| title | Efficient True Resistivity Prediction and Time Optimization in PcRI Measurements: A Results-Driven Approach |
| topic | 2025 SCA Poster |
| url | https://doi.org/10.5281/zenodo.16814401 |