Formation Model Calibration for Adaptive Drilling Trajectory Planning
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Solution Overview
Problem
Existing methods for subsurface reservoir characterization and drilling operations lack accuracy and efficiency, particularly in complex geologic environments with lateral variations and fractures, leading to suboptimal drilling trajectories and resource extraction plans.
Innovation Solution
A computational framework integrating multiple drilling and simulation tools (DRILLPLAN, DRILLOPS, PETREL, TECHLOG, PETROMOD, ECLIPSE, INTERSECT) for enhanced subsurface modeling, visualization, and real-time data integration, enabling precise well trajectory planning and dynamic adjustment during drilling operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional subsurface modeling methods are used, then the modeling process is simpler, but the accuracy of subsurface characterization deteriorates
Solution Approach 1:
The computational framework is segmented into multiple specialized modules (DRILLPLAN for trajectory planning, DRILLOPS for operations management, PETREL for reservoir modeling, TECHLOG for data management, PETROMOD for basin modeling, ECLIPSE for reservoir simulation, and INTERSECT for seismic interpretation). Each module handles specific aspects of subsurface characterization, allowing the system to achieve high accuracy through distributed specialized processing rather than a monolithic approach.
Solution Approach 2:
The integrated computational framework serves multiple functions simultaneously: it performs seismic data interpretation, reservoir modeling, well trajectory planning, drilling operations management, and production simulation. This multi-functional system replaces multiple separate tools with a unified platform that enhances subsurface characterization accuracy across all operational phases.
2Adaptability or versatility
If static formation models are used, then the modeling process is faster, but the ability to adapt to real-time drilling conditions deteriorates
Solution Approach 1:
The framework implements continuous feedback loops where drilling data acquired during operations is fed back into the formation models for real-time calibration and updating. This allows the system to adapt to actual subsurface conditions encountered during drilling, adjusting trajectories and operations dynamically based on measured data from the wellbore and surrounding formations.
Solution Approach 2:
The system transitions from static formation models to dynamic, time-dependent models that evolve as drilling progresses. The computational framework continuously updates subsurface representations based on real-time drilling parameters, geophysical measurements, and operational data, enabling adaptive planning and execution of drilling operations.
3Productivity
If manual interpretation methods are used, then the process is easier to operate, but the productivity of resource extraction planning deteriorates
Solution Approach 1:
The framework replaces manual interpretation and planning methods with automated computational systems that process seismic data, perform reservoir modeling, and optimize drilling trajectories using advanced algorithms and simulations. This substitution of manual mechanical processes with automated computational mechanics significantly enhances productivity in resource extraction planning.
Solution Approach 2:
The system performs preliminary analysis, modeling, and optimization before drilling operations begin. By pre-planning well trajectories, predicting subsurface conditions, and optimizing drilling parameters through comprehensive simulations, the framework enables more efficient and productive resource extraction operations from the outset.
Data Source
AI summary
A method may include receiving a request to generate a calibrated formation model; responsive to the request, providing an initial formation model, providing field data, generating simulation results using the initial formation model, and performing a comparison between the field data and the simulation results; and, based at least in part on the comparison, generating a calibrated formation model.