Utilizing look-up tables representing all models in an automation control architecture to independently handle uncertainties in sensed data in oil and gas well construction

Patent metadata

Field	Value
Publication number	US-10185306-B2
Application number	US-201615053500-A
Country	US
Kind code	B2
Filing date	Feb 25, 2016
Priority date	Feb 27, 2015
Publication date	Jan 22, 2019
Grant date	Jan 22, 2019

Abstract

A method, system and computer program product for utilizing look-up tables representing all models in an automation control architecture to independently handle uncertainties in sensed data. Data is stored in a form of conditional probability tables (CPTs) or conditional probability distributions (CPDs), where the data comes from an operator, a service provider, a drilling contractor and an equipment manufacturer. Models of the drilling process domains, such as wellbore hydraulics, drill bit/rock interactions, torque and drag modeling, vibration modeling and drilling machinery operation, are received. Data is extracted from these models into the CPTs or CPDs. The CPTs or CPDs are converted to look-up tables. Data in the look-up tables are then visually displayed in graphical form. As a result, real-time troubleshooting of drilling operations occurs in an efficient manner.

First claim

The invention claimed is:

1. A method for utilizing look-up tables representing all models in an automation control architecture to independently handle uncertainties in sensed data, the method comprising:
storing data in a form of conditional probability tables or conditional probability distributions, wherein said data comes from all the following sources: an operator, a service provider, a drilling contractor and an equipment manufacturer, wherein said data from said operator comprises information regarding well planning and construction, wherein said data from said service provider comprises data from surface sensors and downhole telemetry tools, wherein said data from said drilling contractor comprises data regarding a working condition of rig equipment, wherein said data from said equipment manufacturer comprises data regarding equipment performance characteristics, wherein said conditional probability tables are matrices or multi-dimensional arrays that represent probabilistic relationships between various drilling parameters, wherein said conditional probability distributions are continuous variants of said conditional probability tables;
receiving models of a drilling process comprising the following domains: wellbore hydraulics, drill bit/rock interactions, rock/fluid interactions, wellbore geomechanics, torque and drag modeling, vibration modeling and drilling machinery operation;
extracting data from said models into said conditional probability tables or conditional probability distributions;
converting, by a processor, said conditional probability tables or conditional probability distributions into look-up tables;
visually displaying data in said look-up tables in graphical form;
generating a set point vector for control variables using real-time data gathered from said surface sensors, model data from said conditional probability tables or conditional probability distributions and a current drilling operation state or event; and
sending control signals based on said control variables to actuators and valves that are controlled to modify a plant's or drilling rig's response to external inputs and noise.

2. The method as recited in claim 1 further comprising:
checking said data for ensuring said data can be trusted; and
detecting said current drilling operation state or event.

3. The method as recited in claim 1 , wherein said models are generated through offline solving of algebraic or differential equations, experimentation or data from offset wells.

4. The method as recited in claim 1 , wherein said automation control architecture applies to drilling, completion, stimulation and production activities.

5. A computer program product for utilizing look-up tables representing all models in an automation control architecture to independently handle uncertainties in sensed data, the computer program product comprising a computer readable storage medium having program code embodied therewith, the program code comprising the programming instructions for:
storing data in a form of conditional probability tables or conditional probability distributions, wherein said data comes from all the following sources: an operator, a service provider, a drilling contractor and an equipment manufacturer, wherein said data from said operator comprises information regarding well planning and construction, wherein said data from said service provider comprises data from surface sensors and downhole telemetry tools, wherein said data from said drilling contractor comprises data regarding a working condition of rig equipment, wherein said data from said equipment manufacturer comprises data regarding equipment performance characteristics, wherein said conditional probability tables are matrices or multi-dimensional arrays that represent probabilistic relationships between various drilling parameters, wherein said conditional probability distributions are continuous variants of said conditional probability tables;
receiving models of a drilling process comprising the following domains: wellbore hydraulics, drill bit/rock interactions, rock/fluid interactions, wellbore geomechanics, torque and drag modeling, vibration modeling and drilling machinery operation;
extracting data from said models into said conditional probability tables or conditional probability distributions;
converting said conditional probability tables or conditional probability distributions into look-up tables;
visually displaying data in said look-up tables in graphical form;
generating a set point vector for control variables using real-time data gathered from said surface sensors, model data from said conditional probability tables or conditional probability distributions and a current drilling operation state or event; and
sending control signals based on said control variables to actuators and valves that are controlled to modify a plant's or drilling rig's response to external inputs and noise.

6. The computer program product as recited in claim 5 , wherein the program code further comprises the programming instructions for:
checking said data for ensuring said data can be trusted; and
detecting said current drilling operation state or event.

7. The computer program product as recited in claim 5 , wherein said models are generated through offline solving of algebraic or differential equations, experimentation or data from offset wells.

8. The computer program product as recited in claim 5 , wherein said automation control architecture applies to drilling, completion, stimulation and production activities.

9. A system, comprising:
a memory unit for storing a computer program for utilizing look-up tables representing all models in an automation control architecture to independently handle uncertainties in sensed data; and
a processor coupled to the memory unit, wherein the processor is configured to execute the computer program instructions comprising:
storing data in a form of conditional probability tables or conditional probability distributions, wherein said data comes from all the following sources: an operator, a service provider, a drilling contractor and an equipment manufacturer, wherein said data from said operator comprises information regarding well planning and construction, wherein said data from said service provider comprises data from surface sensors and downhole telemetry tools, wherein said data from said drilling contractor comprises data regarding a working condition of rig equipment, wherein said data from said equipment manufacturer comprises data regarding equipment performance characteristics, wherein said conditional probability tables are matrices or multi-dimensional arrays that represent probabilistic relationships between various drilling parameters, wherein said conditional probability distributions are continuous variants of said conditional probability tables;
receiving models of a drilling process comprising the following domains: wellbore hydraulics, drill bit/rock interactions, rock/fluid interactions, wellbore geomechanics, torque and drag modeling, vibration modeling and drilling machinery operation;
extracting data from said models into said conditional probability tables or conditional probability distributions;
converting said conditional probability tables or conditional probability distributions into look-up tables;
visually displaying data in said look-up tables in graphical form;
generating a set point vector for control variables using real-time data gathered from said surface sensors, model data from said conditional probability tables or conditional probability distributions and a current drilling operation state or event; and
sending control signals based on said control variables to actuators and valves t

Assignees

• Univ Texas

Inventors

• Ashok Pradeepkumar
• Van Oort Eric
• Ambrus Adrian
• Pournazari Parham
• Shor Roman

Classifications

• E21B44/02 Primary

  Automatic control of the tool feed ({E21B44/005,} E21B44/10 take precedence) · CPC title

• G05B19/4155 Primary

  characterised by program execution, i.e. part program or machine function execution, e.g. selection of a program · CPC title

• G05B2219/45129

  Boring, drilling · CPC title