Prediction of porosity and water saturation of chalks from combined refraction seismic and reflection ground-penetrating radar measurements

التفاصيل البيبلوغرافية
العنوان: Prediction of porosity and water saturation of chalks from combined refraction seismic and reflection ground-penetrating radar measurements
المؤلفون: Hemin Yuan, Abdurrahman Zango Abdu, Lars Nielsen
المصدر: GEOPHYSICS. 88:MR141-MR153
بيانات النشر: Society of Exploration Geophysicists, 2023.
سنة النشر: 2023
مصطلحات موضوعية: Geophysics, Geochemistry and Petrology
الوصف: The prediction of porosity and water content of near-surface chalks is important for agricultural, environmental, hydrologic, and geologic engineering investigations. However, current methods based on laboratory measurements or crosshole ground-penetrating radar (GPR) are typically costly and applicable to only a limited area. We have combined the refraction seismic and reflection GPR data sets measured on the ground surface along a 96 m long profile line to predict the porosity and water saturation simultaneously. Using integrated rock-physics templates, we develop and apply a quantitative method that combines acoustic and electromagnetic velocities to estimate the petrophysical parameters of chalks. The seismic and GPR data are processed independently and subsequently combined to invert the porosity and water saturation. Field data tests demonstrate that the predicted results are consistent with laboratory measurements and field observations, demonstrating that the integration of seismic and GPR data facilitates efficient and reliable estimates of the porosity and saturation of chalks on scales relevant to regional field mapping. Hence, this method allows the petrophysical parameters of near-surface chalks to be evaluated efficiently at a regional scale.
تدمد: 1942-2156
0016-8033
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::80d0f10832de0a0b1e51f97990a6060c
https://doi.org/10.1190/geo2022-0405.1
رقم الأكسشن: edsair.doi...........80d0f10832de0a0b1e51f97990a6060c
قاعدة البيانات: OpenAIRE