CHEMO-MECHANICAL CHANGE PREDICTIONS BY VOXEL BASED NUMERICAL SIMULATION ON OIL WELL CEMENT
A chemo-mechanical change prediction system includes a characterization module operable to receive characterization information of a cement sample, a digital twin builder operable to receive 2D micro-CT data of a cement sample, the digital twin builder including an aggregator configured construct a 3D digital twin of the cement sample from the 2D micro-CT data and the characterization information. a DRP (digital rock physics) module operable to apply image-based computational techniques to the digital twin to segment various image components thereof into separate label fields for quantitative analysis, and an analyzer configured to determine chemo-mechanical changes in the cement sample due to exposure to carbon dioxide (CO2) and/or hydrogen (H2).
1 . A method for making chemo-mechanical change predictions in cement comprising:
a) making a cement sample;
b) characterizing the cement sample using bulk analysis to generate characterization information of the cement sample;
c) performing a micro-CT scan of the cement sample to generate 2D micro-CT data;
d) using a processor to build a digital twin using the characterization information and 2D micro-CT data; and
e) exposing the cement sample to carbon dioxide (CO 2 ) and/or hydrogen (H 2 );
f) repeating b)-d) to build an exposed digital twin; and
g) determining chemo-mechanical changes in the cement based on digital twin microstructural changes.
2 . The method of claim 1 , wherein the microstructural changes include porosity changes.
3 . The method of claim 1 , wherein determining chemo-mechanical changes comprises quantifying the amount of mechanical property change to the microstructural changes to carbon dioxide (CO 2 ) and hydrogen (H 2 ) flow rate and duration.
4 . The method of claim 1 , further comprising simulating exposure to carbon dioxide (CO 2 ) and hydrogen (H 2 ) using the digital twin.
5 . The method of claim 1 , wherein the digital twin comprises a 3D digital volume having a resolution of 0.5, 1, or 5 um/voxel.
6 . The method of claim 1 , wherein the bulk analysis techniques include one or more of X-Ray Diffraction (XRD), Mercury Injection capillary pressure (MICP), Scanning Electron Microscopy (SEM) and Gas Porosimetry.
7 . The method of claim 1 , further comprising conducting simulation to determine one or more of flow properties, filter properties, diffusion properties, conductive properties, acoustic properties, elastic properties, compaction properties, or porosity properties.
8 . The method of claim 7 , further comprising using artificial intelligence to select an optimum solver for the simulation.
9 . A chemo-mechanical change prediction system comprising:
a characterization module operable to receive characterization information of a cement sample;
a digital twin builder operable to receive 2D micro-CT data of a cement sample, the digital twin builder including an aggregator configured construct a 3D digital twin of the cement sample from the 2D micro-CT data and the characterization information;
a DRP (digital rock physics) module operable to apply image-based computational techniques to the digital twin to segment various image components thereof into separate label fields for quantitative analysis; and
an analyzer configured to determine chemo-mechanical changes in the cement sample due to exposure to carbon dioxide (CO 2 ) and/or hydrogen (H 2 ).
10 . The system of claim 9 , further comprising:
a simulator operable to use the digital twin to simulate effects of exposure to carbon dioxide (CO 2 ) and/or hydrogen (H 2 ).
11 . The system of claim 9 , further including an AI/ML engine operable to accelerate simulation speed and/or reduce simulation memory requirements.
12 . The system of claim 9 , wherein the digital twin comprises a 3D digital volume having a resolution of 0.5, 1, or 5 um/voxel.
13 . The system of claim 10 , wherein the simulator is configured to determine one or more of flow properties, filter properties, diffusion properties, conductive properties, acoustic properties, elastic properties, compaction properties, or porosity properties.
14 . The system of claim 13 , further including an AI/ML engine operable to select an optimum solver for simulation by the simulator.
15 . A machine-readable storage medium having stored thereon a computer program for making chemo-mechanical change predictions in cement, the computer program comprising a routine of set instructions for causing the machine to perform the steps of:
a) obtaining characterization information that characterizes a cement sample based on bulk analysis;
b) building a digital twin using the characterization information and 2D micro-CT data of the cement sample;
c) repeating a)-b) to build an exposed digital twin; and
d) determining chemo-mechanical changes in the cement based on digital twin microstructural changes.
16 . The machine-readable storage medium of claim 15 , wherein the microstructural changes include porosity changes.
17 . The machine-readable storage medium of claim 15 , wherein determining chemo-mechanical changes comprises quantifying the amount of mechanical property change to the microstructural changes to carbon dioxide (CO 2 ) and hydrogen (H 2 ) flow rate and duration.
18 . The machine-readable storage medium of claim 15 , the set of instructions further causing the machine to perform the step of:
simulating exposure to carbon dioxide (CO 2 ) and hydrogen (H 2 ) using the digital twin.
19 . The machine-readable storage medium of claim 15 , wherein the digital twin comprises a 3D digital volume having a resolution of 0.5, 1, or 5 um/voxel.
20 . The machine-readable storage medium of claim 15 , wherein the bulk analysis includes one or more of X-Ray Diffraction (XRD), Mercury Injection capillary pressure (MICP), Scanning Electron Microscopy (SEM) and Gas Porosimetry.