Drilling Planning Framework for Real-Time Trajectory Control
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Solution Overview
Problem
Existing technologies face challenges in accurately modeling and optimizing drilling operations in complex subsurface environments, particularly in characterizing reservoirs with lateral variations and fractures, which affects the efficiency and precision of well construction.
Innovation Solution
A framework that integrates computational frameworks such as DRILLPLAN, DRILLOPS, PETREL, TECHLOG, PETROMOD, ECLIPSE, and INTERSECT to automate and optimize drilling operations, including real-time data analysis and simulation, allowing for dynamic planning and execution of drilling tasks based on live feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computational frameworks are integrated to automate drilling operations, then productivity and efficiency are improved, but device complexity increases
Solution Approach 1:
The patent integrates multiple computational frameworks (DRILLPLAN, DRILLOPS, PETREL, TECHLOG, PETROMOD, ECLIPSE, INTERSECT) into a unified automated drilling operations system. This merging of separate software tools and workflows enables comprehensive data integration, real-time simulation, and automated decision-making, thereby improving productivity while managing the inherent complexity through systematic integration.
Solution Approach 2:
The integrated computational framework performs multiple functions including data acquisition, reservoir modeling, drilling simulation, trajectory optimization, and real-time monitoring. By creating a multi-functional system that consolidates these diverse capabilities, the patent achieves improved drilling efficiency without requiring separate standalone systems for each function.
2Manufacturing precision
If real-time data analysis and simulation are implemented, then manufacturing precision of well trajectory is improved, but use of energy and computational resources increases
Solution Approach 1:
The system performs preliminary simulations and analyses using historical and pre-acquired data to predict drilling behavior and optimize trajectories before actual drilling begins. This preliminary action reduces the need for intensive real-time computational resources during drilling operations, as many decisions are pre-determined through advance simulation and modeling.
Solution Approach 2:
The integrated framework implements real-time feedback loops where drilling data is continuously acquired, analyzed, and used to adjust drilling parameters and trajectory. This feedback mechanism improves trajectory precision by comparing actual drilling performance against simulation predictions and making dynamic adjustments, while optimizing computational resource usage through efficient data processing pipelines.
Data Source
AI summary
A method may include receiving a request to select a piece of equipment for performing a field operation at a site; responsive to the request, automatically generating scenarios for a number of candidate pieces of equipment, executing simulations to generate simulation results for the scenarios, and, based at least in part on the simulation results, computing performance indicators for the scenarios; and outputting the performance indicators according to a schema for rendering graphics to a display.