GEODYN: A Geological Formation/Drillstring Dynamics Computer Program

Baird, J.A.; Caskey, B.C.; Tinianow, M.A.; Stone, C.M.

doi:10.2523/13023-ms

Cited by 15 publications

(4 citation statements)

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“…Among these, McLamore [ 33 1 , Bradley [ 34, 39 1 and Smith and Cheatham [40] considered the side force generated on the bit tooth, using simplified 2-D (upper bound) analysis in plasticity. More recently, a large scale computer program was developed to carry out numerical analyses [41,421 to study the simulated dynamic response of PDC bits. The results are also not easily interpreted in te~ of quantitative deviation trends.…”

Section: B Research On Quantitative Prediction Of Deviation Tendencymentioning

confidence: 99%

Prediction of Drilling Trajectory in Directional Wells Via a New Rock-Bit Interaction Model

Ho¹

1987

Proceedings of SPE Annual Technical Conference and Exhibition

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Ibis paper presents the basic concepts and methodologies of a new general rock-bit interaction model useful in predicting drilling trajectories in directional (and deep vertical) wells. This model is a generalization of existing similar models. It accounts for the anisotropic drilling characteristics of both the fo~tion and the bit. 'Itle model is developed in a 3-D geometry. Therefore, it is capable of predicting the walk tendency and the build/drop tendency of a given BHA (bottomhole assembly) under any drilling condition. The model can be used as follows: in the forward mode to predict the drilling direction; in the inverse mode to generate the rock and bit anisotropy indices;in the log-generation mode to generate drilling logs, such as a drilling dip ·log. Examples of the first two uses are shown.

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Section: B Research On Quantitative Prediction Of Deviation Tendencymentioning

confidence: 99%

Prediction of Drilling Trajectory in Directional Wells Via a New Rock-Bit Interaction Model

Ho¹

1987

Proceedings of SPE Annual Technical Conference and Exhibition

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“…(1) actual operating expenses and overhead costs incurred by the service company; (2) charges to recoup R&D investment by the service company; and 3what the service company perceives the developer is willing to pay.…”

Section: Roboticsmentioning

confidence: 99%

“…systems have been developed; (2) no system e x i s t s , but manual methods a r e adequate and the use of an expert system i s not necessary; o r (3) the (1) proprietary potential savings predicted i n this study (based on Adams, 1985)…”

Section: Savings Of Artificial Intelligience Systemsmentioning

confidence: 99%

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Potential impacts of artificial intelligence expert systems on geothermal well drilling costs:

Satrape¹

1987

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The Geothermal Research Program of the U.S. Department of Energy (DOE) has as one of its goals to reduce the cost of drilling geothermal wells by 25 percent. To attain this goal, DOE continuously evaluates new technologies to determine their potential in contributing to the Program. One such technology is artificial intelligence (AI), a branch o f computer science that, in recent years, has begun to impact the marketplace in a number of fields. Two subsets of AI with potential application to geothermal drilling are expert systems and intelligent machines. Expert systems techniques can (and in some cases, a1 ready have) been appl ied to develop computer-based "advisors" to assi st drilling personnel in areas such as designing mud systems, casing plans, and cement programs, optimizing drill bit selection and bottom hole assembly (BHA) design, and alleviating lost circulation, stuck pipe, fishing, and cement problems. Intelligent machines with sensor and/or robotics directly 1 inked to AI systems, have potential applications in areas o f bit control, rig hydraulics, pipe handling, and pipe inspection. Using a well costing spreadsheet, the potential savings that could be attributed to each of these systems was calculated for three base cases: a dry steam well at The Geysers, a medium-depth Imperial Valley well, and a deep Imperial Valley well. The calculations incorporated costs associated with drilling problems, and assumed that each AI system evaluated would succeed in attaining specific efficiency goals. Based on the average potential savings to be realized, expert systems for handling lost circulation problems and for BHA design are the most likely to produce significant results. Other expert systems, specifically for bit optimization and mud design, would also yield significant savings but will likely be available (or already are) from the oil and gas drilling industry. Effort should concentrate on extending these existing systems to geothermal applications. Automated bit control and rig hydraulics also exhibit high potential savings, but these savings are extremely sensitive to the assumptions of improved drilling efficiency and the cost of these systems at the rig.

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Drillstring Vibrations: Classic Ideas and Modern Approaches

Chin¹

2014

Wave Propagation in Drilling, Well Logging and Reservoir Applications

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GEODYN: A Geological Formation/Drillstring Dynamics Computer Program

Cited by 15 publications

References 0 publications

Prediction of Drilling Trajectory in Directional Wells Via a New Rock-Bit Interaction Model

Prediction of Drilling Trajectory in Directional Wells Via a New Rock-Bit Interaction Model

Potential impacts of artificial intelligence expert systems on geothermal well drilling costs:

Drillstring Vibrations: Classic Ideas and Modern Approaches

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