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US 2019/0055461 A1Published application
Systems and methods of optimizing y-grade ngl unconventional reservoir stimulation fluids
AssigneesJohn A. BABCOCK, Linde Aktiengesellschaft
InventorsJohn A. BABCOCK, Charles P. SIESS, III, Kevin G. WATTS, Roberta WATTS
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Abstract
Systems and methods of optimizing stimulation fluids in the form of a hydrocarbon foam, an emulsion based foam, an emulsion, and a gelled stimulation fluid, each comprising Y-Grade NGL, which is an unfractionated hydrocarbon mixture that comprises ethane, propane, butane, isobutane, and pentane plus, wherein the unfractionated hydrocarbon mixture is a byproduct of a condensed and demethanized hydrocarbon stream.
Claims47
A method of optimizing a Y-Grade NGL stimulation fluid, comprising:
- gathering geostatic data and reservoir fluid data of a hydrocarbon bearing reservoir;
- assessing availability of a supply of Y-Grade NGL and a gas;
- using the reservoir fluid data and data regarding the composition of the Y-Grade NGL and the gas to determine an equation of state;
- generating a hydrocarbon foam through a foam generation module, wherein the foam generation module includes customizing a surfactant to be mixed with the Y-Grade NGL and the gas to form the hydrocarbon foam, adjusting foam stability of the hydrocarbon foam, customizing the hydrocarbon foam, and determining a foam rheology of the hydrocarbon foam;
- formulating computational algorithms for the equation of state and the foam rheology;
- formulating a 3-D unconventional reservoir simulation model as represented by the geostatic data, previously matched historical production and pressure data, and the computational algorithms to simulate a reservoir stimulation of the unconventional reservoir using the hydrocarbon foam;
- and
- running multiple simulations for different hydrocarbon foams generated by the foam generation module to determine which hydrocarbon foam will obtain an optimum fluid recovery.
5 more elements
A method of optimizing a Y-Grade NGL stimulation fluid, comprising:
- gathering geostatic data and reservoir fluid data of a hydrocarbon bearing reservoir;
- assessing availability of a supply of Y-Grade NGL, a gas, and water;
- using the reservoir fluid data and data regarding the composition of the Y-Grade NGL, the gas, and the water to determine an equation of state;
- generating an emulsion based foam through an emulsion based foam generation module, wherein the emulsion based foam generation module includes customizing a surfactant to be mixed with the Y-Grade NGL, the gas, and the water to form the emulsion based foam, adjusting foam stability of the emulsion based foam, customizing the emulsion based foam, and determining an emulsion based foam rheology of the emulsion based foam;
- formulating computational algorithms for the equation of state and the emulsion based foam rheology;
- formulating a 3-D unconventional reservoir simulation model as represented by the geostatic data, previously matched historical production and pressure data, and the computational algorithms to simulate a reservoir stimulation of the unconventional reservoir using the emulsion based foam;
- and
- running multiple simulations for different emulsion based foams generated by the emulsion based foam generation module to determine which emulsion based foam will obtain an optimum fluid recovery.
5 more elements
A method of optimizing a Y-Grade NGL stimulation fluid, comprising:
- gathering geostatic data and reservoir fluid data of a hydrocarbon bearing unconventional reservoir;
- assessing availability of a supply of Y-Grade NGL and water;
- using the reservoir fluid data and data regarding the composition of the Y-Grade NGL and the water to determine an equation of state;
- generating an emulsion through an emulsion generation module, wherein the emulsion generation module includes customizing a surfactant to be mixed with the Y-Grade NGL and the water to form the emulsion, adjusting stability of the emulsion, customizing the emulsion, and determining a rheology of the emulsion;
- formulating computational algorithms for the equation of state and the emulsion rheology;
- formulating a 3-D unconventional reservoir simulation model as represented by the geostatic data, previously matched historical production and pressure data, and the computational algorithms to simulate a reservoir stimulation of the unconventional reservoir using the emulsion;
- and
- running multiple simulations for different emulsions generated by the emulsion generation module to determine which emulsion will obtain an optimum fluid recovery.
5 more elements
A method of optimizing a Y-Grade NGL stimulation fluid, comprising:
- gathering geostatic data and reservoir fluid data of a hydrocarbon bearing unconventional reservoir;
- assessing availability of a supply of Y-Grade NGL;
- using the reservoir fluid data and data regarding the composition of the Y-Grade NGL to determine an equation of state;
- generating a Y-Grade NGL stimulation fluid through a Y-Grade NGL generation module, wherein the Y-Grade NGL generation module includes customizing the Y-Grade NGL to form the Y-Grade NGL stimulation fluid and determining a Y-Grade NGL rheology of the Y-Grade NGL stimulation fluid;
- formulating computational algorithms for the equation of state and the Y-Grade NGL rheology;
- formulating a 3-D unconventional reservoir simulation model as represented by the geostatic data, previously matched historical production and pressure data, and the computational algorithms to simulate a reservoir stimulation of the unconventional reservoir using the Y-Grade NGL stimulation fluid;
- and
- running multiple simulations for different compositions of Y-Grade NGL stimulation fluids generated by the Y-Grade NGL generation module to determine which Y-Grade NGL stimulation fluid will obtain an optimum fluid recovery.
5 more elements
Dependencies are inferred from the claim text.