Identifying Effective MWD and LWD Tools for Optimal Well Placement in the Surat Basin, Australia

While deep azimuthal resistivity (DAR) tools remain valuable in complex or high-cost drilling environments, advances in real-time interpretation and geosteering now allow operators to optimize tool selection without sacrificing well placement accuracy. This study demonstrates how a data-driven, fit-for-purpose approach can significantly lower drilling costs in coal seam gas (CSG) developments within Australia’s Surat Basin while maintaining precise well placement.

Real-time azimuthal gamma-ray (Azi-GR) and resistivity data were used to generate deterministic and stochastic resistivity inversions for the Rock-21 well. Both methods leverage a stratigraphy-based correlation by projecting logs into true-vertical-thickness (TVT) space and aligning them with reference wells. This constrains resistivity responses to known formation markers, yielding geologically consistent bed-boundary models. Stochastic inversion extends this by generating multiple probabilistic realizations in data-sparse intervals.

The deterministic inversion delivered earlier and more reliable coal-seam boundary detection, improving trajectory control and reducing non-productive time. Optimized tool selection cut total well costs by 1–3% while sustaining over 95% in-zone performance. By aligning measurement complexity with geological certainty, operators can achieve both economic and technical efficiency—advancing digital well delivery and cost-effective CSG development.