Fluid loss requirement of a cement slurry using bulk blend materials

Patent metadata

Field	Value
Publication number	US-12406751-B2
Application number	US-202117500116-A
Country	US
Kind code	B2
Filing date	Oct 13, 2021
Priority date	Oct 13, 2021
Publication date	Sep 2, 2025
Grant date	Sep 2, 2025

Abstract

A method may include providing a fluid loss model, providing a fluid loss requirement, generating a cement slurry recipe using the fluid loss model and the fluid loss requirement such that a calculated fluid loss of the cement slurry recipe using the fluid loss model meets or exceeds the fluid loss requirement; and preparing a cement slurry based on the cement slurry recipe.

First claim

What is claimed is:

1. A method of designing a cement slurry comprising:
(a) selecting at least a cementitious material and concentration thereof, a water and concentration thereof, and a fluid loss control additive and concentration thereof to form a cement slurry recipe;
(b) calculating a fluid loss of the cement slurry recipe using a fluid loss model, wherein the fluid loss model comprises an equation of the following form:

FL
=

(

∑
i

F
⁢

L
0
i

⁢

P
i

)

⁢

(

w

∑
i

α
i

⁢

P
i

)

n

⁢

exp
⁡
(

γ
⁢
C

)

where FL is fluid loss, FL 0 i is a constant for each cementitious material i in the cement slurry, P i is concentration of cementitious material i in the cement slurry recipe, w is amount of water in the cement slurry recipe, α i is a constant, γ is a measure of effectiveness of fluid loss control additive, n is a constant, and C is a concentration of fluid loss control additive in the cement slurry recipe;
(c) comparing the fluid loss of the cement slurry recipe to a fluid loss requirement, wherein steps (a)-(c) are repeated if the fluid loss of the cement slurry recipe does not meet or stay below the fluid loss requirement, wherein each repeated step of selecting comprises selecting different concentrations and/or different chemical identities for the fluid loss control additive, cementitious material, or water than previously selected, or step (d) is performed if the fluid loss of the cement slurry recipe meets or stays below the fluid loss requirement;
(d) preparing a cement slurry based on the cement slurry recipe, wherein the cement slurry has the property of having fluid loss at or below the fluid loss requirement; and
(e) introducing the cement slurry into a subterranean formation, wherein the cement slurry sets to form a hardened mass.

2. The method of claim 1 wherein the cement slurry recipe further comprises one or more additives is selected from the group consisting of weighting agents, lightweight additives, gas-generating additives, mechanical-property-enhancing additives, lost-circulation control materials, filtration-control additives, defoaming agents, foaming agents, thixotropic additives, dispersants, suspending aids, viscosifiers, transition time control additives and combinations thereof.

3. The method of claim 1 wherein the fluid loss model comprises an equation of the following form:
FL=FL 0 h(w,P)*exp(γC)

where FL is fluid loss, FL 0 is a constant, γ is a measure of effectiveness of fluid loss control additive, C is a concentration of fluid loss control additive, h( ) is a function, w amount of water and P is amount of cementitious material or the sum amount of the cementitious materials (P i ) when more than one cementitious material is present.

4. The method of claim 3 , wherein h( ) is at least one of a polynomial function, power law function, exponential function, logarithmic function, trigonometric function, transcendental function, analytic expression, a neural net, a decision tree, or a combination thereof.

5. The method of claim 1 wherein the fluid loss model further comprises an equation of the following form:
FL=FL 0 *g(C i )

where FL is fluid loss FL 0 is a constant C i is concentration of fluid loss control additive and g( ) is at least one of a polynomial function, power law function, exponential function, logarithmic function, trigonometric function, transcendental function, analytic expression, a neural net, a decision tree, or a combination thereof.

6. The method of claim 1 wherein the fluid loss model further comprises an equation of the following form:
FL=FL 0 *1/(1+βC i )

where FL is fluid loss FL 0 is a constant C i is concentration of fluid loss control additive, and b is a constant associated with physico-chemical properties of the fluid loss control additive.

7. The method of claim 1 wherein the fluid loss model further comprises an equation of the following form:
FL=FL 0 *exp(−βC i )

where FL is fluid loss FL 0 is a constant C i is concentration of fluid loss control additive, and b is a constant associated with physico-chemical properties of the fluid loss control additive.

8. The method of claim 1 further comprising placing the cement slurry in a subterranean formation.

9. A method comprising:
(a) providing a fluid loss model;
(b) providing a fluid loss requirement;
(c) generating a cement slurry recipe using the fluid loss model and the fluid loss requirement such that a calculated fluid loss of the cement slurry recipe using the fluid loss model meets or stays below the fluid loss requirement, wherein the fluid loss model comprises an equation of the following form:

FL
=

(

∑
i

F
⁢

L
0
i

⁢

P
i

)

⁢

(

w

∑
i

α
i

⁢

P
i

)

n

⁢

exp
⁡

Assignees

• Halliburton Energy Services Inc

Inventors

• Singh John Paul Bir
• Jandhyala Siva Rama Krishna

Classifications

• G16C20/70

  Machine learning, data mining or chemometrics · CPC title

• C09K8/487 Primary

  Fluid loss control additives; Additives for reducing or preventing circulation loss · 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

• C04B40/0032

  Controlling the process of mixing, e.g. adding ingredients in a quantity depending on a measured or desired value (B28C7/00 takes precedence) · CPC title

• G16C20/30 Primary

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