Reactivity mapping

Patent metadata

Field	Value
Publication number	US-12545826-B2
Application number	US-202318204656-A
Country	US
Kind code	B2
Filing date	Jun 1, 2023
Priority date	Feb 22, 2017
Publication date	Feb 10, 2026
Grant date	Feb 10, 2026

Abstract

Reactivity mapping methods are provided. A method may include: analyzing each of a group of inorganic particles to generate data about physical and/or chemical properties of the inorganic particles; and generating correlations between the properties of inorganic particles based on the data.

First claim

What is claimed is:

1 . A system comprising:
a predictive model database comprising predictive model data, correlations between properties, and raw data, wherein the correlations comprise at least a water requirement as a function of specific surface area, wherein the water requirement is determined by a process comprising: preparing a blender with a specified amount of water; agitating the water at a specified rate; adding a powdered solid comprising one or more of the inorganic particles to the water until a specified consistency is obtained; and calculating the water requirement based on a ratio of the amount of water to an amount of the powdered solid required to reach the specified consistency; a materials database comprising a plurality of inorganic particles; a computer system configured to query the predictive model database and the materials database and accept input from a user; and an algorithm capable of generating a calculated cement composition using reactivity mapping comprising a cementitious reactive index to obtain a requested tensile strength in accordance with a procedure described in ASTM C307, wherein the cementitious reactive index is a correlation of a cementitious material's reactivity with a specific surface area of the cementitious material.

2 . The system of claim 1 wherein the algorithm is configured to improve the calculated cement composition by generating a cement composition based on a cost objective of the calculated cement composition.

3 . The system of claim 1 wherein the algorithm is configured to improve the calculated cement composition by selecting materials from the materials database.

4 . The system of claim 1 wherein the algorithm is configured to:
analyze the input from the user;
analyze the data from the predictive model database, the data comprising one or more of the predictive model database, the correlations, and/or the raw data; and
output the calculated cement composition.

5 . The system of claim 4 wherein the predictive model includes models of an effect other than a contribution to a cementitious reaction.

6 . The system of claim 4 wherein the predictive model includes a correlation of a specific surface area and water requirement of at least one of the inorganic particles.

7 . The system of claim 1 wherein the predictive model database further comprises average particle size, particle size distribution, and morphology for the plurality of inorganic particles.

Assignees

• Halliburton Energy Services Inc

Inventors

• Pisklak Thomas Jason
• Benkley James Robert
• Brenneis Darrell Chad
• Morgan Ronnie Glen
• Jimenez Walmy Cuello
• Singh John P

Classifications

• E21B33/14

  for cementing casings into boreholes · CPC title

• E21B33/138

  Plastering the borehole wall; Injecting into the formation · CPC title

• C04B28/02 Primary

  containing hydraulic cements other than calcium sulfates · CPC title

• G16C60/00

  Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation · CPC title

• G16C20/30

  Prediction of properties of chemical compounds, compositions or mixtures · CPC title