An apparatus for producing and analyzing sample materials may comprise a milling device for milling material components, a first metering device for metering a material component into the milling device, a second metering device for metering an activator liquid into the milled material component, a homogenization device for homogenizing the material components and the activator liquid to produce a sample material, a control device that is connected to the milling device and is configured to vary a parameter characteristic for milling intensity of the milling device so that particle size of the material components is altered, and a measuring device for determining a reactivity of the sample material. The present disclosure further concerns a process for producing and analyzing a plurality of sample materials. The process may involve varying at least one parameter characteristic for milling intensity for each sample material produced.

Methods may include defining operational parameters for an initial composition design; generating an initial composition design from the defined operational parameters; predicting the performance of the initial composition design using a statistical model; comparing the performance of the initial composition design with the operational parameters; optimizing the initial composition design according to the defined operational parameters; and outputting a final composition design. Methods may also include defining operational parameters for an initial composition design for a wellbore fluid; generating an initial composition design from the defined operational parameters; predicting the performance of the initial composition design using a statistical model; comparing the performance of the initial composition design with the operational parameters; optimizing the initial composition design according to the defined operational parameters; and outputting a final composition design.

Methods may include defining operational parameters for an initial composition design; generating an initial composition design from the defined operational parameters; predicting the performance of the initial composition design using a statistical model; comparing the performance of the initial composition design with the operational parameters; optimizing the initial composition design according to the defined operational parameters; and outputting a final composition design. Methods may also include defining operational parameters for an initial composition design for a wellbore fluid; generating an initial composition design from the defined operational parameters; predicting the performance of the initial composition design using a statistical model; comparing the performance of the initial composition design with the operational parameters; optimizing the initial composition design according to the defined operational parameters; and outputting a final composition design.

Techniques of the present disclosure relate to validating data for a composition design. A method comprises applying a machine learning model to at least two inputs comprising parameters of a cement composition and experimental conditions such that the machine learning model outputs at least one predicted property of the cement composition; performing a laboratory experiment to determine at least one experimental property of the cement composition; calculating an error between the at least one predicted property and the at least one experimental property; and recording the experimental data in a cement property database if the error is within an error range or repeating the performing the laboratory experiment if the error is outside the error range.

For each of a plurality of production facilities, a series of operations is performed. For each of a plurality of batches of a concrete mixture produced at the respective production facility based on a formulation, a first difference between a measured quantity of cementitious and a first quantity specified in the formulation is determined. A first standard deviation is determined based on the first differences. For each of the plurality of batches, a second difference between a measured quantity of water and a second quantity specified in the formulation is determined. A second standard deviation is determined based on the second differences. A first benchmark is selected from among the first standard deviations, and a second benchmark is selected from among the second standard deviations. An amount by which costs may be reduced by improving production at the production facility to meet the first and second benchmarks is determined.

Methods of wellbore cementing are provided. A method of cementing may comprise calculating a lime to silica correlation for two or more cementitious components of a cement composition; and adjusting a concentration of at least one of the cementitious components such that the lime to silica correlation meets or exceeds a target.

Methods of wellbore cementing are provided. A method of cementing may comprise calculating a lime to silica correlation for two or more cementitious components of a cement composition; and adjusting a concentration of at least one of the cementitious components such that the lime to silica correlation meets or exceeds a target.

The invention relates to a method for adjusting concrete rheology requiring only that load size and target rheology value be selected initially rather than requiring inputs into and consultation of a lookup table of parameters such as water and hydration levels, mix components, temperature, humidity, aggregate components, and others. Dosage of particular rheology-modifying agent or combination of rheology-modifying agents is calculated based on a percentage of a nominal dose calculated with reference to a nominal dose response (“NDR”) curve or profile. The NDR profile is based on a correlation between a rheology value (e.g., slump, slump flow, yield stress) and the rheology-modifying agent(s) dose required to change rheology value by one unit (e.g., slump change from 2 to 3 inches) such that exemplary methods can employ corrective dosing based on the NDR and the measured deviation by the system.

The invention relates to a method for adjusting concrete rheology requiring only that load size and target rheology value be selected initially rather than requiring inputs into and consultation of a lookup table of parameters such as water and hydration levels, mix components, temperature, humidity, aggregate components, and others. Dosage of particular rheology-modifying agent or combination of rheology-modifying agents is calculated based on a percentage of a nominal dose calculated with reference to a nominal dose response (“NDR”) curve or profile. The NDR profile is based on a correlation between a rheology value (e.g., slump, slump flow, yield stress) and the rheology-modifying agent(s) dose required to change rheology value by one unit (e.g., slump change from 2 to 3 inches) such that exemplary methods can employ corrective dosing based on the NDR and the measured deviation by the system.

The present invention provides a fast response method and system wherein one or more comb-type polycarboxylate ether (PCE) polymers, having a cumulative absorptivity coefficient in the range of 40%-75%, are employed as fluidizing admixtures dosed into concrete by and in automated slump monitoring and control systems which iteratively monitors and adjusts the slump of the concrete mix.