Although the petroleum geologist is concerned with analysing three-dimensional data, he relies entirely on two-dimensional portrayals - cross-sections and particularly contour maps of all types. With the advent of digital computers, machine contouring has become increasingly common, but little attention has been directed to the limitations of the various algorithms that can be employed to generate contour maps from a set of control points. For example, it is not widely appreciated that contouring procedures which faithfully honour the value of original control points produce poor predictions at locations where no control is available. Contouring a published set of topographic data shows how this and other limitations lead to approximations and errors in machine-generated contours.A new method based on triangulation interpolation using Delaunay tessellations (deltri analysis) is superior to existing methods. Not only does the method give the most accurate and objective measurement and display of the contoured surface, but it is also computationally efficient. Rapid calculation of volume of closure over contoured structures is possible. The method also allows estimation of the adequacy of the data on which the contouring is based by introducing a measure of 'roughness' of the surface. This is achieved by analysing the directions of normals to triangles surrounding each control point.
An indispensable item for every roughneck is the tally book, used to measure and count the drill pipe entering and exiting the wellbore. The current practice is for a crew member to measure the pipe with a pipe strap and enter the information, each time while tripping, into their tally book. This manual entry is prone to error, leading to potential mistakes in the calculated drilling depth and poorly sequenced lithologies, which in turn may contribute to an unsafe environment and drill bit damage due to inaccurate drillstring length. These mistakes often require an additional trip out of hole and increase the amount of nonproductive time. Computer vision technology has shown promise in other industries with its ability to automate similar recognition and counting tasks. A dual-use system has been developed where the same cameras for pipe counting can be used for red zone entry detection, holding the potential to enhance the overall safety of the drilling process. A pilot application has been created serving dual applications: both counting and measuring the pipe entering the wellbore and detecting personnel movement in the red zone during pipe delivery operations. Each stage of the design process was intently developed, considering requirements for both functionalities of the system. Neural network detection algorithms, 3D localization, and drilling data signal processing all combined to interpret rig state and use the appropriate computer vision algorithms at the correct time. System practicalities such as camera placement, hardware and software robustness, and field-tested accuracy were considered. The system has been deployed for field testing in West Texas. The system succeeded in both accurately maintaining a drill pipe count and detecting personnel in the red zone. The system is designed so that the neural network algorithms can be updated using newly collected data as new scenarios are encountered, such as new weather conditions, lighting environments, additional people on the rig floor, and other dynamic factors. This computer vision technology is the first of its kind on a drilling rig. No other system has been developed that accomplishes not only one of the functions, but also two. Just as we have seen rapid improvements each year in driver assistance technology, the time has come to apply recent advancements in computer vision capabilities to increase the efficiency and overall safety of the rig.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.