Imaging Radial Distribution of Water Saturation and Porosity Near the Wellbore by Joint Inversion of Sonic and Resistivity Logging Data
- Sushil Shetty (schlumberger-doll research) | Lin Liang (schlumberger-doll research) | Tarek M Habashy (schlumberger-doll research) | Vanessa Simoes (Schlumberger) | Austin J Boyd (Schlumberger) | Bikash K Sinha (Schlumberger-Doll Research) | Smaine Zeroug (schlumberger-doll research) | Clive Sirju (BG Group) | Tim N Pritchard (BG Group) | Brent Glassborrow (BG Group)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- October 2016
- Document Type
- Journal Paper
- 713 - 730
- 2016.Society of Petroleum Engineers
- formation damage, multiphysics inversion, resistivity, sonic, filtrate invasion
- 0 in the last 30 days
- 384 since 2007
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We present a work flow for joint inversion of sonic flexural-wave dispersion data and array-induction resistivity data acquired in a vertical well. The work flow estimates a pixel-based radial distribution of water saturation and porosity extending several feet into the formation at each log depth. Radial changes in saturation and porosity are caused by mud-filtrate invasion and mechanical damage, respectively. The flexural-wave and array-induction data have similar multiple investigation depths extending several feet into the formation. Furthermore, flexural-wave data are sensitive to porosity but have weak sensitivity to saturation, whereas induction data are sensitive to both porosity and saturation. Thus, integration of these data in a joint inversion can help to characterize the formation beyond the altered zone and reduce uncertainty of the interpretation. The work flow is validated on synthetic data for several scenarios of near-wellbore alteration. The work flow is then applied to field data from an offshore well drilled with oil-based mud in a gas-bearing clastic formation. The results are compared with traditional interpretation and core analysis, demonstrating an efficient and accurate inversion-based work flow that can complement traditional formation evaluation in challenging conditions.
|File Size||2 MB||Number of Pages||13|
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