Chlorite Growth Pattern Study via In-Situ Observation and Simulation
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Solution Overview
Problem
Current methods for studying chlorite growth patterns in sandstone are limited by the inability to accurately capture dynamic evolution patterns and lack of quantitative models for actual geological conditions, leading to inaccurate and incomplete results.
Innovation Solution
A study method combining in-situ high-precision observation with water-rock numerical simulation technology to quantify chlorite growth under actual geological conditions, involving steps such as sample selection, data preprocessing, establishing a water-rock numerical simulation model, and analyzing simulation results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional geological methods are used to characterize current geological results, then qualitative and semi-quantitative observation can be achieved, but the dynamic evolution pattern in the chlorite growth process cannot be accurately captured
Solution Approach 1:
The patent creates a virtual copy of the geological system through numerical simulation, allowing dynamic evolution processes to be observed and analyzed without disturbing the actual system. The simulation model replicates chlorite growth dynamics under controlled conditions, enabling capture of temporal evolution patterns that traditional static observation cannot achieve.
Solution Approach 2:
The patent introduces numerical simulation technology as an intermediary between traditional observation and dynamic evolution analysis. This intermediary layer translates static geological data into dynamic process information, bridging the gap between current state characterization and historical evolution reconstruction.
2Adaptability or versatility
If numerical simulation is used to describe mineral formation and transformation, then various geological conditions can be modeled, but the simulation results often lack quantitative models of actual geological conditions and do not match the actual geological environment
Solution Approach 1:
The patent implements a feedback mechanism where simulation results are continuously compared with actual geological observations and data. This feedback loop allows for calibration and refinement of simulation parameters, ensuring that the virtual model progressively converges toward accurate representation of real geological conditions. The iterative process adjusts model inputs based on discrepancies between simulation and observation.
Solution Approach 2:
The patent systematically adjusts and optimizes simulation parameters based on actual geological data. By changing key parameters such as temperature, pressure, fluid composition, and reaction kinetics to match measured values from field studies, the simulation model transitions from theoretical to quantitatively accurate representation of actual geological environments.
3Ease of operation
If traditional geological methods and numerical simulation are used separately, then each method can be applied independently, but the results are limited and inaccurate
Solution Approach 1:
The patent merges traditional geological observation methods with numerical simulation technology into an integrated study framework. The combination allows qualitative observations to constrain and guide quantitative simulations, while simulation results provide dynamic context for interpreting static observations. This synergistic integration produces comprehensive and accurate conclusions that neither method could achieve alone.
Data Source
AI summary
The present invention belongs to the technical field of petroleum and natural gas exploration and development, and specifically relates to a study method for chlorite growth pattern based on an in-situ high-precision observation means. The method includes: S1: selecting a sample and quantitatively characterizing mineral components; S11: selecting a typical sandstone sample developed with a chlorite coating and cement, grinding a rock slice, and observing under a microscope and a scanning electron microscope to determine a basic morphological characteristic, occurrence state and type of the chlorite; S2: performing data preprocessing on the sample; S3: establishing a water-rock numerical simulation model; S4: developing a water-rock numerical simulation experiment; S5: analyzing a water-rock numerical simulation result; and S6: explaining and applying the water-rock numerical simulation result.