Boundary Detection Ahead of the Bit – A Sensitivity Study of Extra Deep Azimuthal Resistivity

Geosteering and Mapping of Complex Reservoir Boundaries Using an Integrated Data Approach

During drilling, to maximize future expected production of hydrocarbon resources, the experts commonly adjust the trajectory (geosteer) in response to new insights obtained through real-time measurements. Geosteering workflows are increasingly based on the quantification of subsurface uncertainties during real-time operations. As a consequence, operational decision-making is becoming both better informed and more complex. This paper presents an experimental web-based decision support system, which can be used to both teach expert decisions under uncertainty or further develop decision optimization algorithms in a controlled environment. A user of the system (either human or AI) controls the decisions to steer the well or stop drilling. Whenever a user drills ahead, the system produces simulated measurements along the selected well trajectory which are used to update the uncertainty represented by model realizations using the ensemble Kalman filter. To enable informed decisions the system is equipped with functionality to evaluate the value of the selected trajectory under uncertainty with respect to the objectives of the current experiment. To illustrate the utility of the system as a benchmark, we present the initial experiment, in which we compare the decision skills of geoscientists with those of a recently published automatic decision support algorithm. The experiment and the survey after it showed that most participants were able to use the interface and complete the three test rounds. At the same time, the automated algorithm outperformed 28 out of 29 human participants. Such an experiment is not sufficient to draw conclusions about practical geosteering but is nevertheless useful for geoscience. First, this communication-by-doing made 76% of respondents more curious about and/or confident in the presented technologies. Second, the system can be further used as a benchmark for sequential decisions under uncertainty. This can accelerate development of algorithms and improve the training for decision making.

An interactive sequential-decision benchmark from geosteering

Geosteering workflows are increasingly based on the quantification of subsurface uncertainties during real-time operations. As a consequence operational decision making is becoming both better informed and more complex. This paper presents an experimental web-based decision support system, which can be used to both aid expert decisions under uncertainty or further develop decision optimization algorithms in controlled environment. A user of the system (either human or AI) controls the decisions to steer the well or stop drilling. Whenever a user drills ahead, the system produces simulated measurements along the selected well trajectory which are used to update the uncertainty represented by model realizations using the ensemble Kalman filter. To enable informed decisions the system is equipped with functionality to evaluate the value of the selected trajectory under uncertainty with respect to the objectives of the current experiment. 
To illustrate the utility of the system as a benchmark, we present the initial experiment, in which we compare the decision skills of geoscientists with those of a recently published automatic decision support algorithm. The experiment and the survey after it showed that most participants were able to use the interface and complete the three test rounds. At the same time, the automated algorithm outperformed 28 out of 29 qualified human participants. 
Such an experiment is not sufficient to draw conclusions about practical geosteering, but is nevertheless useful for geoscience. First, this communication-by-doing made 76% of respondents more curious about and/or confident in the presented technologies. Second, the system can be further used as a benchmark for sequential decisions under uncertainty. This can accelerate development of algorithms and improve the training for decision making.


 This paper describes a novel approach in drilling production wells while implementing real-time mapping of the Bitumen-Water Contact (BWC) with extra-deep azimuthal resistivity (EDAR) logging while drilling (LWD) service, thereby resulting in an increase of exploited bitumen reserves by optimizing wellbore placement. Within the Athabasca Bitumen Reservoir, the EDAR LWD service confidently mapped the BWC within a range of 2-22 meters below the entire producer wellbore. It also provided an earlier warning of an approaching low resistivity boundary, which allowed the operator to optimize the wellbore placement using real-time proactive steering decisions. In contrast to the existing azimuthal resistivity tools, which have the limited depth of investigation, this approach significantly mitigated the risks of intersecting or giving an incomplete picture of BWC surface. The real-time interpretation of extra-deep azimuthal resistivity data provided better understanding of the lateral distribution of the McMurray Formation along the horizontal wellbore, lithologically varying from clean sand facies to mud-filled channel facies and inclined heterolithic stratification (IHS) facies. The fluid heterogeneity of the reservoir included partial reservoir charging, irregular BWC and lean zones, which compounded lithology complexity within the reservoir. In one of the case studies, 50 percent increase was achieved in actual exploited bitumen reserves in comparison to the projected exploited reserves if drilled per the planned trajectory.
 This new LWD approach was proven effective while drilling horizontal appraisal and producing wells in unconsolidated formations with high reservoir heterogeneity, it offered an opportunity to better understand the bitumen reservoir and ultimately led to increased production performance of Oil Sands projects.

https://onepetro.org/SPETWID/proceedings-pdf/18TWID/1-18TWID/D013S003R004/2347714/spe-193374-ms.pdf

Increase Exposed Bitumen Reserves by Optimizing Wellbore Placement in Oil Sands with Extra-Deep Azimuthal Resistivity LWD Service

Navigating the Horizontal Section in a Heterogeneous Formation While Using Extra Deep Azimuthal Resistivity for Optimizing the Wellbore Placement within a Narrow TVD Window

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Navigating the Horizontal Section in a Heterogeneous Formation While Using Extra Deep Azimuthal Resistivity for Optimizing the Wellbore Placement within a Narrow TVD Window