Presenter
David Holbrough from Baker Hughes
Co-authors
Monica Vik Constable, Brice Fortier, Kåre Røsvik Jensen, Frank Antonsen, Equinor, Warren Fernandes, Tor Eiane, Andreas Hartmann, Yuriy Antonov, Craig Saint, Henrik Andersson, Fredrik Jonsbraten, Baker Hughes
Abstract
Objective/Scope:
Deep & ultra-deep azimuthal resistivity (DAR & UDAR) integrated with automated well placement can aid reservoir understanding and maximise reservoir performance. The reservoir concerned is a highly permeable clastic sand that has many geosteering risks and uncertainties, such as reservoir thickness, varying resistivity (50-1000 Ohmm), and highly permeable zones. The objective for the well was to manage these uncertainties whilst optimizing well placement to within 2m of the roof.
Method, Procedures, Process:
An automated geosteering inversion provides continuous top reservoir tracking while drilling. This allows for the creation of a 3D vector which the rotary steerable closed loop system (RCLS) can follow. This method ensures that changes to the well path are initiated without delay ensuring an optimally placed smooth wellbore that facilitates completions.
Mapping reservoir thickness in the presence of a proximal high resistivity contrast and a distant low resistivity contrast is overcome by utilizing multi-frequency & multi-spacing full-tensor, collocated and pure electromagnetic moments.
A combined deterministic & statistical inversion technique delivered the interpreted lithology or fluid “maps”.
Results, Observations, Conclusions:
The well met its formation evaluation, geosteering and mapping objectives and the variance in reservoir thickness and quality could be determined with increased confidence. Additionally, the well placement objectives were met, with the overall median distance to top reservoir of 0.8m, compared to a target window of 0-2m. As a result of optimal well placement, this well is now considered as a very good producer for the field.
Contributing to this success was not only the application of new LWD and digital technology, with embedded automated workflows – but also the integrated communication across a multi-disciplinary team.
Novel/ Additive Information:
Automated inversions, provides continuous top reservoir boundary tracking while drilling, with creation of a 3D vector tracked by the RCLS.
Acquiring muti-frequency & multi-spacing UDAR data from unique collocated, full-tensor and pure electromagnetic moments adds robustness to the inversion.
New dynamic depth-of-detection, boundary confidence and resistivity analyses helps to quality control the inversions and deliver sensitivity analysis for reservoir volume estimates. Overall, automation enables faster decision making driving improvements in well placement precision.
Biography
David holds a BSc in Geology from the University of Exeter and has 35 years of industry experience with Baker Hughes. He has 28 years international experience in operational roles focusing on top tier Reservoir Navigation across all major basins and led the real-time advisory business in Europe from 2015 to 2020. Currently he is the Senior Global Advisor for Reservoir Navigation working with cross functional teams directing future curriculum, software and technology developments for Reservoir Navigation.