LOW-FREQUENCY DAS SNR IMPROVEMENT

• US 20170342814A1
• Filed: 03/08/2017
• Published: 11/30/2017
• Est. Priority Date: 03/09/2016
• Status: Active Grant

• Current Assignee: Conocophillips Company (ConocoPhillips)
• Original Assignee: Conocophillips Company (ConocoPhillips)
• Inventors: KRUEGER, Kyle R., JIN, Ge, MOSHER, Charles C., SWAN, Herbert W., ROY, Baishali
• Granted Patent: US 10,890,058 B2
• Time in Patent Office: Days
• CPC Class Codes: E21B 43/17 Interconnecting two or more wells by fracturing or otherwise attacking the formation E21B43/2405, E21B43/247 take precedence
• CPC Class Codes: E21B 43/26 by forming crevices or fractures
• CPC Class Codes: E21B 47/114 using light radiation
• CPC Class Codes: E21B 47/135 using light waves, e.g. infrared or ultraviolet waves
• CPC Class Codes: G01H 9/004 using fibre optic sensors light guides per se G02B6/00, acousto-optical devices specially adapted for gating or modulating in optical wave guides G02F1/125
• CPC Class Codes: G01V 1/226 Optoseismic systems
• CPC Class Codes: G01V 1/30 Analysis G01V1/50 takes precedence
• CPC Class Codes: G01V 1/308 Time lapse or 4D effects, e.g. production related effects to the formation fluid flow per se E21B47/00
• CPC Class Codes: G01V 1/42 using generators in one well and receivers elsewhere or vice versa G01V1/52 takes precedence
• CPC Class Codes: G01V 1/48 Processing data
• CPC Class Codes: G01V 2210/1429 Subsurface, e.g. in borehole or below weathering layer or mud line
• CPC Class Codes: G01V 2210/624 Reservoir parameters
• CPC Class Codes: G06T 17/05 Geographic models

Abstract

A workflow using techniques for improving signal-to-noise ratio and decreasing interferences for Low-Frequency Distributed Acoustic Sensing is described.

Claims

1. ) A method of optimizing production of a hydrocarbon-containing reservoir comprising:

a) collecting Low-Frequency Distributed Acoustic Sensing (LF-DAS) data from at least one well in a hydrocarbon-containing reservoir;

b) applying at least one processing technique to said LF-DAS data to form a corrected data set;

c) analyzing said corrected data set; and

,

d) optimizing a production plan for producing hydrocarbons from said reservoir based on said analysis; and

e) implementing said optimized production plan to produce hydrocarbons.

2. ) The method of claim 1, wherein said processing technique is selected from a group comprising median filtering, drift removal, envelope soft limiting, FK filtering, thermal decoupling, dynamic fluid correction, temporal derivatives, and/or amplitude gain control.

3. ) The method of claim 1, wherein step c) further comprises analyzing the corrected data set in combination with at least one of distributed temperature sensor (DTS) measurements, pressure gauge data, and/or microseismic data.

4. ) A method of optimizing the production of a hydrocarbon-containing reservoir comprising:

a) collecting Low-Frequency Distributed Acoustic Sensing (LF-DAS) data from at least one well in a hydrocarbon-containing reservoir;

b) applying at least one processing technique to said LF-DAS data to form a corrected data set, wherein said processing technique is selected from a group comprising median filtering, drift removal, envelope soft limiting, FK filtering, thermal decoupling, dynamic fluid correction, temporal derivatives, and/or amplitude gain control;

c) analyzing said corrected data set; and

,

d) optimizing production of hydrocarbon from said reservoir based on said analysis.

5. ) A method of optimizing production from a hydrocarbon-containing reservoir comprising:

a) installing one or more fiber optic cables in at least one wellbore in a hydrocarbon-containing reservoir;

b) attaching said fiber optic cables to an interrogator having interrogation recording functions;

c) producing hydrocarbon from a target zone in said at least one wellbore using a predetermined parameters of a production scheme;

d) collecting Low-Frequency Distributed Acoustic Sensing (LF-DAS) data from at least one wellbore;

e) interrogating at least one fiber optic cable with an interrogation signal during said performing step;

f) recording one or more LF-DAS datasets;

g) applying at least one processing technique to said LF-DAS datasets to form a corrected dataset;

h) interpreting the corrected dataset to provide an interpreted record;

i) optimizing said predetermined parameters of said production scheme using said interpreted record to provide optimized parameters; and

,

j) using said optimized parameters for producing hydrocarbon from a subsequent zone of said wellbore.

6. ) The method of claim 5, wherein said one or more fiber optic cables are temporarily installed.

7. ) The method of claim 5, wherein said one or more fiber optic cables are permanently installed.

8. ) The method of claim 5, wherein said one or more fiber optic cables are temporarily and/or permanently installed.

9. ) The method of claim 5, wherein said processing technique is selected from a group comprising median filtering, drift removal, envelope soft limiting, FK filtering, thermal recoupling, dynamic fluid correction, temporal derivatives, and/or amplitude gain control

10. ) The method of claim 5, wherein step c) further comprises analyzing the corrected data set in combination with at least one of distributed temperature sensor (DTS) measurements, pressure gauge data, and/or microseismic data.

11. ) A method of optimizing a hydraulic fracturing stimulation of a reservoir comprising:

a) installing one or more fiber optic cables in at least one wellbore;

b) attaching said fiber optic cables to an interrogator having interrogation and reflection recording functions;

c) fracturing a stage of a multistage hydraulic fracturing stimulation in a reservoir using pre-determined parameters;

d) interrogating at least one fiber optic cable with an interrogation signal during said performing step;

e) recording one or more reflected datasets;

f) applying at least one processing technique to said LF-DAS data to form a corrected data set;

g) interpreting the corrected data set to provide an interpreted record;

h) optimizing said pre-determined parameters of said hydraulic fracturing stimulation using said interpreted record to provide optimized parameters; and

,

i) using said optimized parameters for fracturing a subsequent stage in said reservoir.

12. ) The method of claim 11, wherein said one or more fiber optic cables are temporarily installed.

13. ) The method of claim 11, wherein said processing technique is selected from a group comprising median filtering, drift removal, envelope soft limiting, FK filtering, thermal recoupling, dynamic fluid correction, temporal derivatives, and/or amplitude gain control

14. ) The method of claim 11, wherein step c) further comprises analyzing the corrected data set in combination with at least one of distributed temperature sensor (DTS) measurements, pressure gauge data, and/or microseismic data.