Point and Vector Model for Reservoir Data Integration
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Solution Overview
Problem
Current wellbore and completion design operations face challenges in efficiently managing and analyzing large datasets from multiple sources, as traditional relational databases and models are complex and difficult to integrate, limiting the ability to generalize data across reservoirs and requiring extensive computational resources.
Innovation Solution
Implementing a point and vector model in a column-oriented database allows for centralized data storage and analysis, enabling efficient data aggregation, analytics, and reduced computational complexity by representing data points and vectors, which can span large areas and handle microseismic data, and incorporating time-based measurements to optimize completion design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional relational databases and models are used for data storage and analysis, then data can be stored in structured formats, but the system becomes complex and difficult to integrate multiple data sources
Solution Approach 1:
The patent applies a unified point and vector data model that can universally represent diverse geological and engineering data from multiple sources. Instead of using separate relational schemas for different data types, the system uses a single flexible model where data are represented as points with associated vectors, enabling the same structure to handle wellbore data, seismic data, reservoir properties, and completion data across different reservoirs and applications.
Solution Approach 2:
The patent transforms data representation by changing the fundamental parameters from relational table structures to geometric point-vector structures. Data are expressed in terms of spatial coordinates (x, y, z) and directional vectors, allowing dynamic adaptation to different data types and reservoir configurations without requiring complex relational joins or data transformation layers.
2Ease of manufacture
If data are tied to gridded reservoir volumes within a specific formation, then data storage is structured, but it becomes difficult to generalize data outside of that formation
Solution Approach 1:
The point and vector model serves as a universal data representation that is not bound to any specific formation or grid structure. The same model can represent data from different formations, reservoirs, and geological settings by simply changing the coordinate values and vector directions, enabling broad generalization without sacrificing storage organization.
Solution Approach 2:
The patent transitions from formation-specific grid-based storage to a dimensionless point-vector representation. By expressing data in terms of spatial coordinates and directional vectors rather than grid cell indices, the system gains the ability to represent data in any spatial context, enabling seamless generalization across different formations and reservoirs.
3Loss of information
If multiple databases are queried to extract formation properties, then comprehensive data can be retrieved, but the process requires extensive computational resources
Solution Approach 1:
The patent consolidates data from what would traditionally be multiple separate databases into a unified point and vector model. By storing all formation properties, wellbore data, and completion data in a single integrated structure, the system eliminates the need for multiple database queries and reduces computational overhead while maintaining complete data coverage.
Solution Approach 2:
The patent extracts the essential geometric and spatial relationships from complex relational data structures and represents them directly as points and vectors. This extraction removes unnecessary computational layers and intermediate data transformations, allowing direct access to formation properties without querying multiple databases.
4Manufacturing precision
If extensive simulations are performed to optimize wellbore and completion designs, then design accuracy is improved, but the process becomes time-consuming and computationally intensive
Solution Approach 1:
The patent performs preliminary data organization and spatial relationship establishment using the point and vector model before optimization simulations. By pre-processing and structuring data in a unified geometric framework, the system reduces the computational burden of subsequent simulations and enables faster convergence to optimal designs.
Solution Approach 2:
The patent changes the representation parameters of design data from detailed relational schemas to compact point-vector forms. This parameter transformation reduces the dimensionality and complexity of data that must be processed during simulations, maintaining design accuracy while significantly reducing computation time.
Data Source
AI summary
Systems and methods for generating and storing measurements in point and vector format for a plurality of formations of reservoirs. In one embodiment, the methods comprise generating a set of measurements corresponding to a plurality of formations, reservoirs, or wellbores; determining physical locations for the set of measurements, wherein the physical locations are represented in a point and vector representation; associating the vector representations with the determined physical locations, wherein the vector representations comprise at least a magnitude and a direction derived from the measurement; wherein the magnitude and direction tracks the physical location in space and time; manipulating the set of measurements such that a change in physical location is updated in the vector representation; generating a repository of vector representations accessible to determine an optimal completion design for a set of parameters for a subterranean formation.