3D Numerical Pseudocores via Multi-Point Statistics
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Solution Overview
Problem
Current methods for generating 3D numerical cores from borehole images and digital rock samples face challenges in creating realistic reservoir models due to gaps in borehole imaging data and limitations in multi-point statistics (MPS) algorithms, particularly in handling continuous variable training images and capturing decimeter to meter-scale heterogeneities.
Innovation Solution
The method employs fullbore images and digital rock samples using multi-point statistics (MPS) to reconstruct 3D numerical pseudocores, where digital core samples guide feature reconstruction, and the final pseudocores are constrained by fullbore images, leveraging FILTERSIM algorithm for pattern classification and simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multi-point statistics (MPS) algorithms are used to generate 3D numerical cores from borehole images and digital rock samples, then the ability to capture complex geological features is improved, but the handling of continuous variable training images and decimeter to meter-scale heterogeneities remains limited
Solution Approach 1:
The patent transforms the continuous variable training image into a categorical representation by defining multiple facies types (e.g., sand, shale, carbonate) with distinct properties. This parameter transformation allows the MPS algorithm to process the data effectively while preserving the essential geological heterogeneity at decimeter to meter scales. The continuous properties are discretized into facies categories that the simulation algorithm can handle, resolving the contradiction between accuracy and adaptability.
2Reliability
If digital rock samples are used to guide feature reconstruction, then the realism of reservoir models is improved, but the complexity of the reconstruction process increases
Solution Approach 1:
The patent divides the reconstruction process into distinct sequential steps: (1) processing digital rock samples to extract facies information, (2) processing borehole images to obtain structural constraints, (3) running MPS simulation to generate the 3D model, and (4) validating against observed data. This segmentation makes the complex reconstruction process more manageable and systematic while maintaining high realism through the integration of multiple data sources.
3Measurement precision
If fullbore images are used to constrain the final pseudocores, then the accuracy of geological feature representation is improved, but the computational requirements and processing time increase
Solution Approach 1:
The patent performs preliminary processing of the fullbore images before the main MPS simulation, including noise reduction, feature enhancement, and facies classification. By preparing the constraint data in advance, the actual simulation process runs more efficiently while still achieving high accuracy in representing geological features. This preliminary action reduces the computational burden during the time-critical simulation phase.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach generates accurate 3D numerical pseudocores that honor both digital rock and fullbore image data, enabling improved fluid-flow modeling and capturing complex geological features, thereby enhancing the realism and accuracy of reservoir models.
Implementation Method 1
The invention is generally related to a method using a seminal Multi-point statistics (MPS) algorithm to generate numerical pseudocores from digital rock or core samples and borehole-imaging logs
Implementation Method 2
CTscans are 2-dimensional (2D) cross sections generated by an X-ray source that rotates around the sample. Density is computed from X-ray attenuation coefficients.
Data Source
AI summary
Methods and systems for creating a numerical pseudocore model, comprising: a) obtaining logging data from a reservoir having depth-defined intervals of the reservoir, and processing the logging data into interpretable borehole image data having unidentified borehole image data; b) examining one of the interpretable borehole image data, other processed logging data or both to generate the unidentified borehole image data, processing the generated unidentified borehole image data into the interpretable borehole image data to generate warped fullbore image data; c) collecting one of a core from the reservoir, the logging data or both and generating a digital core data from one of the collected core, the logging data or both such that generated digital core data represents features of one or more depth-defined interval of the reservoir; and d) processing generated digital core data, interpretable borehole image data or the logging data to generate realizations of the numerical pseudocore model.