Abstract

At-bit imaging is a unique technology that captures the first engagement of the drilling bottom-hole assembly (BHA) with the subsurface through the integration of sensors in a polycrystalline diamond compact (PDC) drill bit. The sensor acquires high frequency axial force data while scraping freshly exposed rock and formation properties like overburden, lithology, porosity, rock strength and compressibility manifest themselves in the recorded data.

The at-bit imaging sensor operates in challenging environments of variable drilling dynamics, high pressure, high mud flow velocities and abrasive rock contact and the sensor design is a trade-off between reliability and sensitivity. Drilling dynamics also directly affects the sensor engagement with the rock, potentially introducing noise in the recorded data and images. Early field deployment of this technology in carbonate, clastic, poorly consolidated, unconventional and hard-rock geothermal environments provided insights that have led to development in sensor architecture and data processing techniques.

Field deployment of this technology was carefully designed to cover wide range of subsurface formations in different geological settings with many different BHA’s to test both geological applicability and sensor reliability. The downhole data recorded in the sensor memory, covering a wide range of lithologies, downhole conditions, operating parameters and BHAs with different motors and rotary steerable systems were analyzed in detail for both geological features and sensor reliability.

Through analyzing field test data and comparing output from simulations the characteristics and root causes of image noise as well as the effects of sensor sensitivity and resolution are well understood. The performance of the sensor, both pre- and post-run was investigated to identify the feature detection limit in terms of the rock strength contrast the feature provides.

The field data, images and post-run evaluation of the sensors have given a detailed insight into the subsurface geology in addition to reliability and sensitivity of the sensor and the opportunity to study the various modes of downhole dynamics and the characteristics and severity of the undesired image artifacts they introduce.

Structural and sedimentary features like fractures, folds, faults, cross-beds, conglomerates, laminations, vugs, dissolution seams, stylolites, karst etc. have been imaged at highest resolution and quality in the downhole conditions. These images were used in established image interpretation workflows to pick dips, characterize features and produce answers related to petrophysical variability qualitatively to support well operations.

Drilling dynamics related features (non-geologic) were visible in some intervals, a workflow was developed to catalog them against their root cause and remove them in post processing of the data.

This study builds on learnings through early field results of at-bit imaging in various geologic environments and downhole drilling conditions in addition to lab testing and simulations to provide an extended operating environment for the deployment of the technology while developing processing solutions to address the artifacts.