Vendor-Independent Stochastic Inversion Models of Azimuthal Resistivity LWD Data, Case Studies From the Norwegian Continental Shelf

Abstract

Drilling horizontal wells in complex formations is always a challenging task. The development of deep and ultra-deep azimuthal resistivity tools has largely improved the accuracy of the wellbore placement in the target zone. The enhanced imaging provided by the stochastic inversion of the azimuthal resistivity data can be applied for mapping both the internal reservoir structure and fluid contacts in the field. Major oil and gas service companies provide the operator with azimuthal resistivity tools and develop their own algorithms for resistivity data processing. Commonly services companies process azimuthal resistivity data internally. We have developed a vendor-independent stochastic inversion method that is applicable to almost any deep-azimuthal resistivity tools. This module allows operators to carry out real-time geosteering, as well as pre-job and post-job data analyses independently from the service company. This paper demonstrates the examples of the azimuthal resistivity data interpretation using synthetic data and actual data from the well offshore Norway. Calculated inversion models, based on actual data, allowed mapping of the oil-water contact and discontinuities in the reservoir that take place at the resistivity contrast boundaries. The application of this technology can increase the percentage of the horizontal well in the pay zone while letting the operator cut drilling costs through optimizing bottom hole assembly and use more advanced interpretation practices.

Boundary detection capability and influencing factors of electromagnetic resistivity while using drilling tools in a horizontal well

“…The other type, by AziTrak and ViziTrak of Baker Hughes, uses an orthogonal antenna (Bell et al, 2006;Wang et al, 2007;Fang et al, 2008;Rabinovich et al, 2011). According to the detection range, EM boundary detection LWD tools can be divided into the azimuthal electromagnetic resistivity LWD tool (Hawkins et al, 2015) and the ultra-deep azimuthal electromagnetic resistivity LWD detection logging tool (Wu et al, 2019;Nemushchenko et al, 2022;Zhu et al, 2022).…”