(534g) Geosteering Using Image Logs and an Intelligent Bottomhole Assembly

Geo-steering refers to making decisions about directing a horizontal drilling system towards a desired trajectory. Geo-steering decisions are made at the surface by a team of engineers and geologists to direct (control) the bit in the appropriate direction within the reservoir. Logging tools in the bottom hole assembly (BHA) sense oil pockets at the bit, and the BHA moves in a reasonable direction, to drill a well that will drain the maximum possible sweet spots within the reservoir, after production start. Assessing this direction is done by identifying the floor and the ceiling of the reservoir and staying within these limits. This approach has two issues on which improvements can be envisioned: (a) there is considerable dead-time (due to very limited bandwidth of measuring/logging-while-drilling (M/LWD) tools) which reduces achievable control performance, and (b) considerable manpower is required.

The proposed approach attempts to address both of these issue by using an automation system at the BHA, with two capabilities: (a) Process images in real time, to detect floor and ceiling of the reservoir, and (b) perform rapid model predictive control (MPC) calculations, to steer the bit in the right direction.

The proposed approach would eliminate dead-time from the overall geo-steering control loop, thus resulting in tighter control. This would reduce diversion of the bit outside the reservoir pocket, resulting in a well with higher contact area with the reservoir. Benefits for the drilling operation would also result, as the bit would wear less, as there would be less need for demanding excursions from the ideal path, and MTBF for each component of the tool would reduce.

This presentation shows simulations of how this overall architecture would work. Specifically, edge detection and other image processing algorithms are used to detect reservoir floor and ceiling, and MPC is used to minimize both distance from the desired trajectory and overall mechanical energy. Issues on numerical efficiency, computer chip requirements, and overall feasibility are discussed.