Reactivity Mapping

Patent metadata

Field	Value
Publication number	US-2020332172-A1
Application number	US-201716479848-A
Country	US
Kind code	A1
Filing date	Feb 22, 2017
Priority date	Feb 22, 2017
Publication date	Oct 22, 2020
Grant date	—

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 method comprising:
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 inorganic particles based on the data.

2 . The method of claim 1 further comprising generating a statistical table comprising two or more different parameters of the inorganic particles.

3 . The method of claim 1 further comprising preparing a cement composition comprising the inorganic particles and allowing the cement composition to set in a wellbore.

4 . The method of claim 1 wherein at least one of the inorganic particles comprises at least one of silica, alumina, iron, iron oxide, calcium, calcium oxide, sodium, potassium, magnesium, sulfur, and combinations thereof

5 . The method of claim 1 wherein the analyzing the inorganic particles comprises analysis by one or more techniques selected from the group consisting of microscopy, spectroscopy, x-ray diffraction, x-ray fluorescence, particle size analysis, water requirement analysis, scanning electron microscopy, energy-dispersive X-ray spectroscopy, surface area, specific gravity analysis, thermogravimetric analysis, morphology analysis, infrared spectroscopy, ultraviolet-visible spectroscopy, mass spectroscopy, secondary ion mass spectrometry, electron energy mass spectrometry, dispersive x-ray spectroscopy, auger electron spectroscopy, inductively coupled plasma analysis, thermal ionization mass spectroscopy, glow discharge mass spectroscopy x-ray photoelectron spectroscopy, mechanical property testing, Young's Modulus testing, rheological properties, Poisson's Ratio, API testing, and combinations thereof

6 . The method of claim 1 wherein the data comprises an amount of at least component selected from the group consisting of silica, alumina, iron, calcium, sodium, potassium, magnesium, sulfur, oxides thereof, and combinations thereof

7 . The method of claim 1 wherein the data comprises average particle size, particle size distribution, and morphology for each of the inorganic particles.

8 . The method of claim 1 wherein the data comprises specific surface area for each of the inorganic particles.

9 . The method of claim 1 wherein the correlations comprises at least a correlation of specific surface area for each of the inorganic particles to water requirement for each of the inorganic particles.

10 . The method of claim 1 further comprising identifying a cement additive comprising two or more of the inorganic particles, and predicting one or more mechanical properties of a cement composition comprising the cement additive.

11 . The method of claim 1 further comprising identifying a cement additive comprising two or more of the inorganic particles, and estimating reactivity of the cement additive.

12 . The method of claim 1 further comprising identifying a cement additive comprising two or more of the inorganic particles, preparing a sample cement composition comprising the cement additive, testing the cement composition to determine one or more performance characteristics.

13 . The method of claim 1 further comprising identifying a cement additive comprising two or more of the inorganic particles, based at least partially, on the correlations.

14 . The method of claim 1 further comprising mixing a wellbore treatment fluid comprising at least one of the inorganic particles using mixing equipment.

15 . The method of claim 14 further comprising introducing the wellbore treatment fluid into a wellbore using one or more pumps.

16 . A system comprising:
a plurality of inorganic particles; an analytical instrument configured to gather physical and/or chemical data about the inorganic particles; and a computer system configured to accept the physical and/or chemical data and/or generate correlations between the inorganic particles based on the data.

17 . The system of claim 16 wherein at least one of the inorganic particles comprises at least one of silica, alumina, iron, iron oxide, calcium, calcium oxide, sodium, potassium, magnesium, sulfur, and combinations thereof

18 . The system of claim 16 wherein the analytical instrument is configured to perform one or more of functions selected from the group consisting of microscopy, spectroscopy, x-ray diffraction, x-ray fluorescence, particle size analysis, water requirement analysis, scanning electron microscopy, energy-dispersive X-ray spectroscopy, surface area, specific gravity analysis, thermogravimetric analysis, morphology analysis, infrared spectroscopy, ultraviolet-visible spectroscopy, mass spectroscopy, secondary ion mass spectrometry, electron energy mass spectrometry, dispersive x-ray spectroscopy, auger electron spectroscopy, inductively coupled plasma analysis, thermal ionization mass spectroscopy, glow discharge mass spectroscopy x-ray photoelectron spectroscopy, mechanical property testing, Young's Modulus testing , rheological properties, Poisson's Ratio, API testing, and combinations thereof.

19 . The system of claim 16 wherein the computer system further comprises an algorithm configured to:
analyze the physical and/or chemical data and output a predictive model; and
store the predictive model in a predictive model database.

20 . The system of claim 19 wherein the predictive model includes models of an effect other than a contribution to a cementitious reaction.

21 . The system of claim 19 wherein the predictive model includes a correlation of a specific surface area and water requirement of at least one of the inorganic particles.

22 . A system comprising:
a predictive model database comprising predictive model data, correlations between properties, and raw data; a materials database; 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.

23 . The system of claim 22 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.

24 . The system of claim 22 wherein the algorithm is configured to improve the calculated cement composition by selecting materials from the materials database.

25 . The system of claim 22 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.

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

• G16C20/30

  Prediction of properties of chemical compounds, compositions or mixtures · 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

• C04B28/02 Primary

  containing hydraulic cements other than calcium sulfates · CPC title

• E21B33/13 Primary

  Methods or devices for cementing, for plugging holes, crevices or the like · CPC title

• C04B28/04 Primary

  Portland cements · CPC title