A qualitative characteristic scheme and a fast distance prediction method of multi-probe azimuthal gamma-ray logging in geosteering

Azimuthal gamma-ray logging instruments play an important role in the geological steering technology (geosteering) of directional drilling engineering. While their logging response characteristics in various geology bodies are ambiguous, and a fast prediction methods of the distances between logging instruments and formation boudnaries, which are suitable for real time geosteering in drilling, are rare. In order to settle these problems, a Monte Carlo model is established based on the two-layer model and the multi-probe azimuthal gamma-ray logging (MPAGR) instrument structure. Monte Carlo N-Particle Transport (MCNP) Code is employed to simulate the logging responses of MPAGR when drilling into various geology structure bodies (layerd formations, fault, pinchouts and lens), which commonly drilled by honrizontal wells, and then a logging response characteristic scheme in eight spatial relationships between horizontal wells and formations is analyzed and summerized for guiding geosteering qualitatively. Based on these numerical simulations, a fast prediction method, a series of non-linear functions which can describe the relationships between logging responses and boundary distances, is proposed to guide realtime geosteering quantitatively. Finally, the qualitative scheme and the quantitative prediction method are applied in two horizontal wells in the Songliao Basin, China. The application results and effects demonstrate the availability of the scheme and the reliability of the fast prediction method. The scheme and the prediction method can provide reference and alternative solutions for real-time geosteering when drilling horizontal wells, especially in the formations where the geosteering function of resistivity logging is limited, e.g., shale gas/oil, coalbed methane, thin layer and low resistivity contrast reservoirs.