Intelligent Reservoir Classification Platform

The intelligent reservoir classification and evaluation platform adopts deep learning to simulate the professional logic of geological experts, at the same time, it analyzes and models the logging curve and logging image data, and has reservoirs got intelligent division and classification through multi-model fusion technology.

Product Positioning

Taking reservoir evaluation as the starting point and the intelligent processing and interpreting of the logging information as the premise , it solves the two major problems of massive data in multiple wells of the old area and too much individual analysis proportion in the previous conclusions. It improves the work efficiency of technicians effectively and reduces the multiplicity of solutions.

Technical Adaptability

Penetrating the intelligent technology into oil and gas exploration and development, and it has become an indispensable means to solve the basic links of mature exploration areas, deepen reservoir knowledge, serve rolling exploration and efficient development.

Main Functions
Data Source Interface

Well related data files could be read, including logging curves, imaging logging data and manual evaluation results (for comparison).

Data Processing Module

Including missing value processing, gray processing, etc

Visualization Module

To realize the logging data and reservoir classification results visualized, and it mainly includes the original logging curve, reservoir classification and evaluation results, manual analysis results, and the consistency between the model intelligent recognition and manual analysis.

Application Scenario

New well Planning Evaluation

Rechecking the old well to extract
the potential oil reservoir

technology roadmap
Product Advantages
Simple Operation

One click to intelligent divide and identify the reservoir

Strong Interpretation Ability

The use of random forest interpretation model can refine the reservoir discrimination logic and quantitative indicators, which is convenient for users to understand.

Accurate Identification

The reservoir is divided by comprehensively using imaging logging data and logging curve data, and the final division result is obtained after weighting by using random forest algorithm and convolution neural network algorithm.

High Efficient Identification

The platform can complete the processing, division and comprehensive research and judgment of multi-source data of single target well in one minute, and quickly locate all kinds of high-quality reservoirs

Product display