Abstract
Horizontal wells dominate the development of unconventional shale reservoirs. Using real time drilling data to steer in a target zone is the key to economic success. Today structural interpretation in unconventional horizontal wells is a manual process that is time-consuming, tedious, and error-prone, especially because gamma-ray (GR) logs are commonly the only available logging-while-drilling data. For the first time, a method named TST3D is developed to automate interpretation of subsurface structure. TST3D (true stratigraphic thickness in three-dimensional space) automates structural interpretation using pattern recognition. Given an initial structural model, TST3D automatically computes true stratigraphic thickness (TST) as the shortest distance from each wellbore survey location to the initial surface, then matches GR patterns in the horizontal well to those seen in a vertical pilot well in TST domain. TST3D inserts fold hinges, bends the structure, then recomputes the modeled GR response, progressively matching the pilot well log signature, from heel to toe in the horizontal well. There are three assumptions in the current version of TST3D: constant layer thickness across the drilled interval, GR variation follows stratigraphic layering, and no faults are present in the drilled section. Those assumptions are reasonable in most shale plays. The TST3D method can be applied in either a post-drill mode for structural interpretation or real-time mode for aiding geosteering. Field tests in different shale plays and complex well trajectories demonstrate that TST3D runs quickly: a structural model of a 10,000-ft horizontal section can be computed in minutes, and a real-time update of 100 ft of new data takes less than a minute. Automating the geosteering correlation process would allow well placement engineers to cover multiple wells simultaneously, increasing the efficiency of the team while potentially improving service quality.
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Acknowledgements
We thank Schlumberger for the permission to publish our work. We would like to thank Neil Hurley, Ridvan Akkurt, and Shu Zhang for their technical discussion and contribution in the early stage of the development of TST3D. Thanks to Farid Toghi for providing the illustrative dataset of TST3D work steps.
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The original paper was presented to the Unconventional Resources Technology Conference, 23–25 July 2018, Houston, Texas, USA.
Abbreviations
Abbreviations
- GR:
-
Gamma ray measurements, GAPI
- LWD:
-
Logging while drilling
- MD:
-
Measured depth (ft)
- TVD:
-
True vertical depth (ft)
- TST:
-
True stratigraphic thickness (ft)
- MLT:
-
Measured log thickness (ft)
- TVT:
-
True vertical thickness (ft)
- TVDT:
-
True vertical depth thickness (ft)
- THL:
-
True horizontal length (ft)
- TD:
-
Total depth (ft)
- \(\phi \) :
-
Wellbore deviation (\(\circ \))
- \(\alpha \) :
-
Angle difference between the bedding azimuth and the wellbore section azimuth (\(\circ \))
- \(\theta \) :
-
Bedding dip (\(\circ \))
- N :
-
Total number of the measurement samples in a TST split panel interval
- ARE:
-
Average relative error for the mismatch between the GR measurements and the models in TST domain
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Zhang, T., McCormick, D., Nandlal, A. et al. The TST3D Method for Automated Structural Interpretation in Horizontal Wellbores. Math Geosci 53, 925–944 (2021). https://doi.org/10.1007/s11004-020-09868-z
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DOI: https://doi.org/10.1007/s11004-020-09868-z