Noise estimation in a vector sensing streamer

• US 7,466,625 B2
• Filed: 06/23/2006
• Issued: 12/16/2008
• Est. Priority Date: 06/23/2006
• Status: Expired due to Fees

• Current Assignee: WesternGeco LLC
• Original Assignee: WesternGeco LLC
• Inventors: Teigen, Oeyvind, Robertsson, Johan Olof Anders
• Primary Examiner(s): Keith; Jack W
• Assistant Examiner(s): Hughes; Scott A
• Application Number:
  US11/426,058
• Publication Number:
  US 20070297287A1
• Time in Patent Office: 907 Days
• Field of Search: 367/24, 367/58, 367/153, 367/15, 367/20, 181/104, 702/18
• US Class Current: 367/24
• CPC Class Codes: G01V 1/201 Constructional details of seismic cables, e.g. streamers integrated optoseismic systems G01V1/226; line connectors in general H01R, transducer mountings in general G10K11/004
• CPC Class Codes: G01V 1/36 Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
• CPC Class Codes: G01V 1/3808 Seismic data acquisition, e.g. survey design
• CPC Class Codes: G01V 2210/32 Noise reduction
• CPC Class Codes: G01V 2210/34 Noise estimation quality control G01V2200/14
• CPC Class Codes: G01V 2210/56 De-ghosting; Reverberation compensation

Abstract

A method includes recording a first set of data using a first type of sensor; recording a second set of data using a second type of sensor, the first and second sets of data being contemporaneously acquired by co-located sensors; and removing noise from the first data set using the second data set. An apparatus includes a survey vessel towing an array of towed streamers including a plurality of paired, co-located sensors densely distributed along the streamers. A first one of each sensor pair is of a first type and a second one of each sensor pair is of a second type. A computing apparatus records a first set of data acquire by the first type of sensor and a second data set acquire by the second type of sensor. The computing apparatus then removes noise from the first data set using the second data set.

Claims

1. A method, comprising:

recording a first set of data using a first type of sensor;

recording a second set of data using a second type of sensor, the first and second sets of data being contemporaneously acquired by co-located sensors;

estimating an inline noise component in the first set of data from the second set of data using n_x(t,x_r)=d_x(t,x_r)−

1/ρ

∂

_xP(t,x_r), where d_x(t,x_r) represents recording of a particle sensor in the inline direction, a_x(t,x_r)=1/ρ

∂

_xP(t,x_r), P(t,x_r)represents the inline gradient of acoustic sensor recordings and a_x(t,x_r) represents the inline component of particle acceleration and ρ

represents the density of the medium in which the particle sensor is located; and

correcting the first set of data using the estimated inline noise component.

2. The method of claim 1, wherein recording the first data set using a first type of sensor includes recording a set of pressure data using a hydrophone.

3. The method of claim 1, wherein the second set of data comprises vector data.

4. The method of claim 1, wherein the vector data is recorded using an accelerometer.

5. The method of claim 1, wherein the first set of data comprises vector data.

6. The method of claim 5, wherein the vector data is recorded using an accelerometer.

7. The method of claim 1, wherein recording the second data set using a second type of sensor includes recording a set of pressure data using a hydrophone.

8. The method of claim 1, wherein the first data set is pressure data and the second data set is acceleration data, and further comprising:

determining the in-line gradient of the pressure data to isolate the non-acoustic component of an in-line acceleration measurement;

predicting the noise on the cross-line and vertical components of the acceleration data from the determined in-line gradient of the pressure data; and

correcting the acceleration data for the predicted noise.

9. The method of claim 8, wherein correcting the acceleration data includes subtracting the predicted noise component from the acceleration data.

10. The method of claim 8, wherein the first data set is pressure data and the second data set is acceleration data, and further comprising:

isolating the non-acoustic noise in the acceleration data; and

correcting the pressure data for the non-acoustic noise.

11. The method of claim 10, wherein correcting the pressure data includes subtracting the isolated non-acoustic noise from the pressure data.

12. The method of claim 1, further comprising acquiring the first set of data and the second set of data.

13. The method of claim 12, further comprising transmitting or transporting the acquired data to a remote location for the estimation and correction.

14. The method of claim 1, further comprising transmitting or transporting the first and second data sets to a remote location for the estimation and correction.

15. A program storage medium encoded with instructions that, when executed by a computing apparatus, perform a method comprising:

recording a first set of data using a first type of sensor;

recording a second set of data using a second type of sensor, the first and second sets of data being contemporaneously acquired by co-located sensors;

estimating an inline noise component in the first set of data from the second set of data using n_x(t,x_r)=d_x(t,x_r)−

1/ρ

∂

_xP(t,x_r), where d_x(t,x_r) represents recording of a particle sensor in the inline direction, a_x(t,x_r)=1/ρ

∂

_xP(t,x_r), P(t,x_r)represents the inline gradient of acoustic sensor recordings and a_x(t,x_r) represents the inline component of particle acceleration and ρ

represents the density of the medium in which the particle sensor is located; and

correcting the first set of data using the estimated inline noise component.

16. A computing apparatus, comprising:

a processor;

a bus system;

a storage communicating with the processor over the bus system; and

a software application residing on the storage that, when invoked by the processor, performs a method including;

recording a first set of data using a first type of sensor;

recording a second set of data using a second type of sensor, the first and second sets of data being contemporaneously acquired by co-located sensors;

estimating an inline noise component in the first set of data from the second set of data using n_x(t,x_r)=d_x (t,x_r)−

1/ρ

∂

_xP(t,x_r), where d_x(t,x_r) represents recording of a particle sensor in the inline direction, a_x(t,x_r)=1/ρ

∂

_xP(t,x_r), P(t,x_r) represents the inline gradient of acoustic senor recordings and a_x(t,x_r) represents the inline component of particle acceleration and ρ

represents the density of the medium in which the particle sensor is located; and

correcting the first set of data using the estimated inline noise component.

17. An acquisition system, comprising:

a survey vessel;

an array of streamers towed by the survey vessel;

a plurality of paired, co-located sensors distributed densely along each the streamers, a first one of each sensor pair being a first sensor of a first type and a second one of each sensor pair being a second sensor of a second type, each one of the paired sensors being co-located; and

a computing apparatus, programmed to;

recording a first set of data using the first type of sensor;

recording a second set of data using the second type of sensor;

estimating an inline noise component in the first set of data from the second set of data using n_x(t,x_r)=d_x (t,x_r)−

1/ρ

∂

_xP(t,x_r), where d_x(t,x_r) represents recording of a particle sensor in the inline direction, a_x(t,x_r)=1/ρ

∂

_xP(t,x_r) P(t,x_r) represents the inline gradient of acoustic senor recordings and a_x(t,x_r) represents the inline component of particle acceleration and ρ

represents the density of the medium in which the particle sensor is located; and

correcting the first set of data using the estimated inline noise component.

18. The apparatus of claim 17, wherein the first type of sensor is a seismic sensor.

19. The apparatus of claim 18, wherein the second type of sensor is a vector sensor.

20. The apparatus of claim 17, wherein the first type of sensor is a vector sensor.

21. The apparatus of claim 20, wherein the second type of sensor is a seismic sensor.

22. The apparatus of claim 17, wherein the computing apparatus is aboard the survey vessel.

23. The apparatus of claim 22, wherein the computing apparatus collects the first and second sets of data from the sensors as they are acquired.