MULTIPLE DOWNHOLE SENSOR DIGITAL ALIGNMENT USING SPATIAL TRANSFORMS

• US 20170122099A1
• Filed: 10/30/2015
• Published: 05/04/2017
• Est. Priority Date: 10/30/2015
• Status: Active Grant

• Current Assignee: Baker Hughes, a GE Company, LLC (Baker Hughes Company)
• Original Assignee: Baker Hughes Incorporated (Baker Hughes Company)
• Inventors: Sullivan, Eric C., Yao, Richard Jin, Makkar, Navish
• Granted Patent: US 10,392,933 B2
• Time in Patent Office: Days
• CPC Class Codes: E21B 44/00 Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions
• CPC Class Codes: E21B 47/024 of devices in the borehole determining slope or direction of the borehole E21B47/022
• CPC Class Codes: E21B 49/003 by analysing drilling variables or conditions E21B49/005 takes precedence; systems specially adapted for monitoring a plurality of drilling variables or conditions E21B44/00

Abstract

Wellbore sensor systems and related methods are disclosed. A wellbore sensor system includes a first sensor node and a second sensor node. The first sensor node is operably coupled to a drill string at a first location. The second sensor node is operably coupled to the drill string at a second location. A method includes taking first sensor readings from the first sensor node relative to a first spatial frame of reference, and taking second sensor readings from the second sensor node relative to a second spatial frame of reference, and using the first sensor readings and the second sensor readings to estimate parameters of a mathematical transform configured to transform the second sensor readings into the first spatial frame of reference. The method also includes transforming the second sensor readings into the first spatial frame of reference with the estimated mathematical transform.

Claims

1. A wellbore sensor system, comprising:

a drill string operably coupled to a drilling element configured to drill through a formation;

a plurality of sensor nodes including at least;

a first sensor node operably coupled to the drill string at a first location and comprising one or more first sensors including a first spatial sensor;

a second sensor node operably coupled to the drill string at a second location offset from the first location along a length of the drill string, the second sensor node comprising one or more second sensors including a second spatial sensor;

a non-transitory data collection system configured to store sensor data from the plurality of sensor nodes therein; and

one or more control circuits operably configured to receive the sensor data from the first sensor node and the second sensor node, the one or more control circuits each including a processor operably coupled to a data storage device, the data storage device including computer-readable instructions stored thereon and the processor configured to execute the computer-readable instructions stored on the data storage device, the computer-readable instructions configured to instruct the processor to;

estimate, using the sensor data from the first spatial sensor and the second spatial sensor, parameters of a mathematical transform configured to transform sensor readings from the second sensor node in a second spatial frame of reference of the second sensor node into a first spatial frame of reference of the first sensor node; and

transform the sensor readings from the second sensor node into the first spatial frame of reference using the estimated mathematical transform.

2. The wellbore sensor system of claim 1, wherein the plurality of sensor nodes further includes a third sensor node operably coupled to the drill string a third location offset from the first location and the second location along the length of the drill string, wherein the one or more control circuits are further configured to receive the sensor data from the third sensor node, and wherein the computer-readable instructions are further configured to instruct the processor to;

estimate, using the sensor data from the first spatial sensor and the third spatial sensor, parameters of another mathematical transform configured to transform sensor readings from the third sensor node in a third spatial frame of reference of the third sensor node into the first spatial frame of reference; and

transform the sensor readings from the third sensor node into the first spatial frame of reference using the estimated other mathematical transform.

3. The wellbore sensor system of claim 1, wherein frames of reference of each of the plurality of sensor nodes share substantially a same vertical axis.

4. The wellbore sensor system of claim 3, wherein the vertical axis is substantially parallel to a longitudinal length of the drill string.

5. The wellbore sensor system of claim 1, wherein the first sensor node includes the one or more control circuits.

6. The wellbore sensor system of claim 1, wherein the non-transitory data collection system comprises a dedicated, non-transitory memory operably connected to each sensor node and configured to collect and store sensor data therefrom and wherein the one or more control circuits are configured to receive the sensor data from the first sensor node and the second sensor node after drilling is complete.

7. The wellbore sensor system of claim 1, wherein the first spatial sensor and the second spatial sensor each include at least one of an accelerometer, a magnetometer, and a gyroscope.

8. The wellbore sensor system of claim 7, wherein the accelerometer includes a three-axis accelerometer.

9. The wellbore sensor system of claim 1, wherein each of the plurality of sensor nodes includes at least one sensor selected from the list consisting of a pressure sensor, a temperature sensor, an elevation sensor, an electromagnetic sensor, and an acoustic sensor.

10. The wellbore sensor system of claim 1, further comprising a wellbore communication system operably coupled to each of the sensor nodes and configured to transmit the sensor data to the non-transitory data collection system in real time, the wellbore communication system comprising at least one communication system selected from the list consisting of an acoustic communication system, an electrical communication system, a galvanic communication system, and a fiber-optic communication system.

11. The wellbore sensor system of claim 10, wherein each of at least two of the sensor nodes includes a control circuit of the one or more control circuits, wherein the one or more control circuits are configured to communicate with each other through the wellbore communication system.

12. The wellbore sensor system of claim 11, wherein the one or more control circuits are configured to transmit transformed sensor readings to surface equipment through the wellbore communication system.

13. The wellbore sensor system of claim 1, wherein the plurality of sensor nodes further comprises another sensor node located at the drilling element.

14. A method of transforming wellbore sensor data into a common spatial frame of reference, the method comprising:

taking first sensor readings with a first sensor node operably coupled to a drill string at a first location, the first sensor readings taken relative to a first spatial frame of reference of the first sensor node;

taking second sensor readings with a second sensor node operably coupled to the drill string at a second location offset from the first location along the length of the drill string, the second sensor readings taken relative to a second spatial frame of reference of the second sensor node;

executing computer-readable instructions stored on a data storage device with a processor, the computer-readable instructions configured to instruct the processing element to perform operations including;

using the first sensor readings and the second sensor readings to estimate parameters of a mathematical transform configured to transform the second sensor readings into the first spatial frame of reference; and

transforming the second sensor readings into the first spatial frame of reference with the estimated mathematical transform.

15. The method of claim 14, wherein estimating parameters of a mathematical transform comprises estimating differences between spatial orientation and position of the second spatial frame of reference with respect to the first spatial frame of reference for three rotational degrees of freedom and three positional degrees of freedom.

16. The method of claim 14, wherein estimating parameters of a mathematical transform comprises:

estimating frequencies with which the first sensor node and the second sensor node are rotating by analyzing magnetometer data from the first sensor readings and the second sensor readings, respectively;

computing numeric regressions of the magnetometer data from the first sensor readings and the second sensor readings using the estimated frequencies to estimate an instantaneous bias parameter, an acceleration parameter, and a phase parameter of the magnetometer data for each of the first sensor node and the second sensor node;

estimating rotational transforms configured to rotate the second sensor readings taken in the second spatial frame of reference such that coordinate axes of the second spatial frame of reference are parallel to corresponding coordinate axes of the first spatial frame of reference;

estimating positional transforms configured to shift the second sensor readings taken in the second spatial frame of reference such that a vertex of the coordinate axes of the second spatial frame of reference coincides with a vertex of the coordinate axes of the first spatial frame of reference; and

applying the rotational transforms and the positional transforms to the second sensor readings to transform the second sensor readings into the first spatial frame of reference.

17. The method of claim 16, wherein computing numeric regressions of the magnetometer data comprises performing at least one of regressions and nonlinear regressions.

18. The method of claim 16, wherein estimating rotational transforms comprises computing a normal, orientation, approach computation to rotate and align the second sensor readings for two degrees of rotational freedom with the first spatial frame of reference.

19. The method of claim 16, wherein:

estimating rotational transforms comprises estimating two separate rotational transforms including a first rotational transform for a first degree of rotational freedom and a second rotational transform for second and third degrees of rotational freedom;

estimating positional transforms comprises estimating separate positional transforms for each of three positional degrees of freedom; and

applying the rotational transforms and the positional transforms to the second sensor readings comprises computing a matrix dot product of each of the rotational transforms and the three positional transforms to obtain a single combined transform, and applying the single combined transform to the second sensor readings.

20. The method of claim 14, further comprising synchronizing a second time monitor of the second sensor node with a first time monitor of the first sensor node.