Integrated Geospatial Map for Hydrocarbon Exploration Assessment
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Solution Overview
Problem
The exploration and evaluation of hydrocarbon resources in diverse geological environments are challenging due to high financial and time commitments, making it difficult for petroleum companies and states to accurately assess and classify potential hydrocarbon-producing locations.
Innovation Solution
A computer-implemented method and system that integrates geospatial maps with data on composite common risk segments, reservoir properties, fluid properties, finding costs, and expected volumes to generate an integrated map, allowing for the determination of hydrocarbon exploration attributes such as yet-to-find values, reserve volumes, and play chances, facilitating informed decision-making for drilling operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional hydrocarbon exploration methods are used, then exploration activities can be conducted, but assessment accuracy and classification reliability are insufficient due to diverse geological environments and high financial commitments
Solution Approach 1:
The patent segments the hydrocarbon exploration assessment into multiple geospatial layers, each representing different data dimensions (geological properties, reservoir characteristics, economic parameters, risk factors). This segmentation allows complex assessment to be broken down into manageable, standardized components that can be evaluated independently and then integrated, improving assessment accuracy while managing complexity through modular processing
Solution Approach 2:
The patent creates a universal geospatial framework that can accommodate diverse geological environments and multiple evaluation criteria within a single integrated system. This multi-functional platform handles various data types (structural, stratigraphic, economic, risk-related) using consistent methodologies, enabling accurate assessment across different exploration contexts without requiring separate evaluation systems for each geological setting
2Loss of information
If comprehensive data collection is performed across multiple geospatial maps, then resource evaluation completeness improves, but data integration complexity and processing time increase
Solution Approach 1:
The patent performs preliminary organization of exploration data into standardized geospatial layers with defined schemas and relationships before integration. By pre-structuring data according to the framework's requirements, the system eliminates time-consuming data cleaning and formatting during the integration phase, allowing comprehensive data collection to be processed efficiently while maintaining complete evaluation coverage
Solution Approach 2:
The patent uses geospatial copying techniques where standardized data models and templates are replicated across different exploration areas. Once a data structure is established for one region, it can be copied and adapted to other regions, significantly reducing processing time for comprehensive data collection while maintaining evaluation completeness through consistent data representation
3Reliability
If multiple geospatial layers are integrated, then resource classification accuracy improves, but system complexity and computational requirements increase
Solution Approach 1:
The patent segments the integrated assessment system into distinct geospatial layers, each handling specific types of information (geological, reservoir, economic, risk). This segmentation allows the system to manage complexity by processing and validating each layer independently according to its specific requirements, then integrating results to achieve reliable classification without overwhelming system complexity
Solution Approach 2:
The patent transitions from traditional two-dimensional map-based assessment to multi-dimensional geospatial analysis by stacking multiple thematic layers vertically. This dimensional transformation allows the system to handle complex relationships between different data types through standardized spatial operations, improving classification reliability while managing complexity through consistent geometric and topological processing rules
Data Source
AI summary
Methods and systems for hydrocarbon resources exploration assessment are provided. Geospatial maps having corresponding hydrocarbon resources data may be obtained and classified. The geospatial maps may include composite common risk segment (CCRS) geospatial maps, reservoir and fluid properties geospatial maps, economics and costing geospatial maps, and prospect and leads geospatial maps. The geospatial maps may be integrated to generate an integrated map having each of geospatial maps as layers. An area of interest (AOI) may be defined on the integrated map and yet-to-find values, reserve volumes, pore volumes, and fluid properties, estimated prospect volumes, play chance and prospect success ratio, and average finding cost and average well cost may be determined for the area of interest (AOI).