Abstract

Abstract A new three-dimensional drillstring model has been developed that determines the static and dynamic behavior of bottom hole assemblies (BHAs) in realistic wellbores. The analysis approach has been validated with field data, and shows a strong agreement between observed and calculated BHA behavior. Several case studies are presented that show the practical use and benefit of the advanced model for, among other applications, unconventional horizontal drilling. A framework is also provided to show how the model can be incorporated into automated engineering processes for operations support. Validation tests were conducted using high-frequency down-hole data measured within a motor- assisted rotary-steerable BHA. The gathered data was used to verify the calculated mechanical loads, predicted lateral natural frequencies of the BHA, estimated directional performance of the down-hole assembly, as well as torsional resonance resulting from High-Frequency Torsional Oscillations (HFTO). Using the validated model, various analyses have been conducted for operators around the globe, in a multitude of different drilling environments, to aid in identifying drilling dysfunctions and optimizing BHA performance. Several case studies are presented that highlight the benefit of the modeling techniques in US unconventional shale plays as well as in the Canadian heavy-oil sands, with noticeable improvements in drilling efficiencies, tool design, and reduced non-productive time (NPT). Results from the field tests show a strong correlation between measured and calculated bending moment values, as well as lateral natural frequencies of the BHA with an average of 3% error across all data sets. The primary source of error is thought to be borehole spiraling, which is quantified through analysis of the down-hole bending moment data. In addition, the model is shown to provide close estimates to actual directional performance of both steerable mud motor and Rotary-Steerable BHAs. However, the directional calculation-measurement comparison does reveal a need to incorporate an ROP-dependency within the directional prediction algorithms. Nevertheless, even with these sources of discrepancy, the modeling approach provides a sensible prediction of the BHA's mechanical and dynamic behavior and, as shown through case studies, can be used as a planning tool for BHA design, an investigative tool for root-cause analysis, or potentially as a real-time optimization tool for avoiding harmful operating conditions.

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