Method for performing optical gauge length selection for fibers used in hydrocarbon recovery operations, carbon capture and sequestration, and geothermal applications - Patent Application 20070122999

Abstract

The presented embodiments provide for the use of optical fibers in a downhole environment. Furthermore, the embodiments provide for selecting an optimal gauge length for optical fibers in hydrocarbon recovery operations, carbon capture and sequestration operations, or geothermal applications. The method includes acquiring data from the optical fiber, processing the data using a fixed gauge length, estimating apparent velocities with an autonomous computing array using the fixed gauge length, estimating source bandwidth from the apparent velocities with the autonomous computing array to generate results, establishing a variable gauge length and reference profile of the results, and processing the acquired data with the established variable gauge length to obtain a processed optical data set.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This patent application is an international application claiming priority to U.S. Provisional Patent Application No. 63 / 370,573, filed August 5, 2022, the entire contents of which are incorporated herein by reference.

[0002] Aspects of the present disclosure relate to optical fibers and their use in hydrocarbon recovery operations, as well as carbon capture and sequestration, and geothermal applications. More particularly, aspects of the present disclosure relate to selecting optimal optical fiber gauge lengths for use in hydrocarbon recovery operations, as well as carbon capture and sequestration, and geothermal applications. [Background technology]

[0003] Distributed vibration sensing (DVS), also known as distributed acoustic sensing (DAS), is an alternative method for recording vertical seismic profile (VSP) data using fiber optic cables as sensors rather than a series of discrete sensors deployed as a borehole seismic array. There have been several implementations of this technique, all based on optical time-domain reflectometry (OTDR). OTDR systems operate by firing a pulse of light down a fiber optic cable. As the pulse travels down the cable, some of the light is scattered due to small fluctuations in the refractive index within the fiber that are "frozen" during the manufacturing process. A small fraction of this light scatters in the opposite direction from the laser, within the fiber's acceptance angle, and then travels back up the fiber to be detected by a receiver. The location of the section of fiber containing the scattering source can be easily calculated from the recording time, the speed of light, and the group index of the glass.

[0004] When the fiber is stationary, the backscattered signal from multiple pulses is random but constant. However, as the cable deforms, the travel time to the section of fiber beyond the deformation point changes, resulting in a change in the backscattered signal. Because the change in amplitude of the backscattered signal has a highly nonlinear transfer function that is unsuitable for seismic applications, the phase difference between two points is used instead. The physical distance between the two points is called the gauge length (GL), as shown in Figure 1.

[0005] Gauge length is often cited as one of the most important parameters to select for DAS acquisitions, especially for specific DAS implementations where such parameters are hardware-defined. Early references confirmed the importance of this parameter for improving the signal-to-noise ratio (SNR), with typical values ranging between 7 m and 35 m. Additional work conducted to investigate the relationship between GL and SNR showed that SNR can be maximized by selecting GL as a fraction of the apparent wavelength, with recommended fractions between 0.4 and 0.6.

[0006] However, most DAS systems can only function with a fixed gauge length (FGL) relative to the overall well depth, but the apparent wavelength is likely to change with depth depending on the subsurface geology, posing two potential problems. The selected GL may either be too short for some receivers, resulting in an insufficient SNR, or the GL may be too long, resulting in distorted signals. In this paper, we first present a novel method for processing data using a variable gauge length (VGL). We then demonstrate the application of this technique using synthetic DAS VSP data. Finally, we present an example of a real field dataset.

[0007] There is a need to provide an apparatus and method that is easier to operate than previous apparatus and methods for fiber optic systems.

[0008] Furthermore, there is a need to provide an apparatus and method that does not have the drawbacks discussed above, namely, extensive manual calculations to ensure valid results.

[0009] There is still a further need to reduce the economic costs associated with operating optical fiber and its operating equipment for hydrocarbon recovery operations as well as carbon capture and sequestration and geothermal applications using conventional tools. Summary of the Invention

[0010] So that the above-recited features of the present disclosure can be understood in detail, a more particular description of the present disclosure will be understood by reference to the embodiments briefly summarized below, some of which are illustrated in the drawings. It should be noted that the drawings illustrate only typical embodiments of the present disclosure, and therefore, these typical embodiments should not be considered as limiting the scope of the present disclosure, and other equally effective embodiments may be recognized without being specifically recited. Therefore, the following summary provides only some aspects of the specification and should not be used to limit the described embodiments to a single concept.

[0011] In one exemplary embodiment, a method for processing data is disclosed. The method may include acquiring data from an optical fiber, processing the data using a fixed gauge length, and estimating an apparent velocity using the fixed gauge length with an autonomous computing array. The method may also provide for estimating a source bandwidth from the apparent velocity with the autonomous computing array to generate a result, and establishing a variable gauge length and reference profile of the result. The method may also provide for processing the acquired optical data with the established variable gauge length to obtain a processed optical data set.

[0012] In another example, a wellbore method is disclosed that includes deploying optical fiber along well equipment and positioning the well equipment in a wellbore that penetrates a region of interest. The method may also include connecting the optical fiber to a distributed vibration sensing system and utilizing a length of the optical fiber to detect signals indicative of vibrations in the region of interest. The method may further include selecting wavelengths of interest of the detected signals as a function of the length of the optical fiber to generate and apply a variable gauge length profile to phase data obtained from the detected signals, the variable gauge length profile defining a gauge length value that varies as a function of the optical fiber length. The method may also include using the variable gauge length profile to process the phase data obtained from the length of the optical fiber, and processing the phase data obtained from a particular section using a gauge length value associated with a particular section of the optical fiber to generate processed phase data, the variable gauge length being calculated through an autonomous computing system that uses an estimated apparent velocity and an estimated bandwidth of the vibrations.

[0013] So that the above-recited features of the present disclosure may be understood in detail, a more particular description of the present disclosure will be understood by reference to the embodiments briefly summarized above, some of which are illustrated in the drawings. It should be noted that the drawings illustrate only typical embodiments of the present disclosure, and therefore, those typical embodiments should not be considered as limiting the scope of the present disclosure, as other equally effective embodiments may be recognized. [Brief explanation of the drawings]

[0014] [Figure 1] This is a cross section of a specified gauge length. [Figure 2] 10 is a flowchart of gauge length selection in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0015] For ease of understanding, where possible, like reference numerals have been used to designate like elements common to the drawings ("FIGS") It is contemplated that elements disclosed in one embodiment may be beneficially utilized on other embodiments without being specifically recited.

[0016] Reference will be made below to embodiments of the present disclosure. However, it should be understood that the present disclosure is not limited to the specifically described embodiments. Instead, any combination of the following features and elements, whether associated with different embodiments or not, is contemplated for implementing and practicing the present disclosure. Furthermore, while embodiments of the present disclosure may achieve advantages over other possible solutions and / or over the prior art, whether or not a particular advantage is achieved by a given embodiment does not limit the present disclosure. Accordingly, the following aspects, features, embodiments, and advantages are merely exemplary and should not be considered claim elements or limitations unless expressly recited in the claims. Similarly, references to "the present disclosure" should not be construed as generic to the inventive subject matter disclosed herein, and should not be considered claim elements or limitations unless expressly recited in the claims.

[0017] Terms such as "first," "second," and "third" may be used herein to describe various elements, components, regions, layers, and / or sections, but these terms are not intended to limit the scope of these elements, components, regions, layers, and / or sections. These terms may be used only to distinguish one element, component, region, layer, or section from another region, layer, or section. When used herein, terms such as "first," "second," and other numerical terms do not imply a sequence or order unless clearly indicated by context. Thus, a first element, component, region, layer, or section described herein may be referred to as a second element, component, region, layer, or section without departing from the teachings of the exemplary embodiments.

[0018] When an element or layer is referred to as "on," "engaged to," "connected to," or "bonded to" another element or layer, it may be directly on, engaged with, connected to, or bonded to the other element or layer, or there may be intervening elements or layers. In contrast, when an element is referred to as "directly on," "directly engaged with," "directly connected to," or "directly bonded to" another element or layer, there may be no intervening elements or layers. Other words used to describe relationships between elements should be interpreted similarly. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed terms.

[0019] Some embodiments will now be described with reference to the drawings. Like elements in various figures will be referenced with like numerals for consistency. In the following description, numerous details are set forth to provide an understanding of various embodiments and / or features. However, one skilled in the art will understand that some embodiments may be practiced without many of these details and that numerous variations or modifications from the described embodiments are possible. As used herein, the terms "above" and "below," "on" and "below," "upper" and "lower," "upward" and "downward," and other similar terms indicating relative positions above or below a given point, are used in this description to more clearly describe particular embodiments.

[0020] Referring to FIG. 1, aspects of the present disclosure include removing certain practical limitations by using an automated algorithm to estimate apparent velocity and bandwidth, such that a locally optimal GL can be calculated without any user intervention, and VGL processing can be fully automated for each receiver and source location independently. An example of this is disclosed in FIG. 2. Referring to FIG. 2, a method 200 for processing data associated with an optical fiber is shown. At 202, optical data is stored, including ZVSP and WAVSP data. At 204, the data from step 202 is processed using a fixed GL. The fixed GL may be, for example, 10 meters. As will be appreciated, other values may be selected and the fixed GL may vary. At 206, the data processed using the fixed GL is used to estimate an approximate velocity using a model. In an embodiment, aspects of the present disclosure provide for estimating the model using an autonomous computational array. In an embodiment, the computational array may be a personal computer or a unit specifically designed to provide such calculations. In an embodiment, these calculations may be further defined or performed using artificial intelligence.

[0021] At 208, the bandwidth is estimated from the results of 206 using the processed data. As with the processing at 206, the processing may be automated and may occur without further operator interaction. At 210, the results from 208 as well as the reference profile corresponding to the variable gauge length are used to establish the variable gauge length. The reference profile from 210 and the selected variable gauge length are used to process the optical data from 202 to obtain processed optical data at 212.

[0022] By means of the above method 200, in an embodiment, a VGL profile is automatically calculated for each source location, allowing for reprocessing of WAVSP or even 4D VSPs that are guaranteed to always maximize the SNR for each receiver and for each source location, instead of relying on ZVSP profiles as is done for traditional in situ data examples.

[0023] In embodiments, several processing methods may be used to achieve this. In one non-limiting embodiment, visco-acoustic modeling may be used. Machine learning may also be used to automate the calculation of the optical gauge length.

[0024] Embodiments may use the VGL concept for non-seismic applications of DAS interrogators. For example, for pipeline integrity applications, one major problem is that noise levels increase with distance as optical losses increase. One way to compensate for such losses without using active or passive optical amplification is to define a VGL profile set to compensate for optical losses, thereby maintaining a flat noise profile with distance. These embodiments result in a decrease in spatial resolution with distance, but this may be acceptable for certain applications, such as intrusion detection, where the ability to detect intrusions is significantly improved at lower noise levels.

[0025] In some embodiments, for flow applications, computational benefits are derived from multi-resolution measurements without the need to reprocess the data. Such analysis can be performed once the data is spatially partitioned. For example, during hydraulic fracturing operations, the main portion of the wellbore may benefit from a longer GL to ensure low noise levels and improved ability to monitor microseismic events, while portions closer to the reservoir targeted for fluid injection may benefit from a shorter GL to ensure improved spatial resolution and improved ability to efficiently identify fractures at specific intervals.

[0026] In embodiments, new methods are used to determine optical gauge length, leveraging variable gauge length processing for different acquisition geometries, as described above. These methods may be used for a variety of conditions, including temporarily deployed fiber, permanently deployed fiber, downhole deployed, surface deployed, and co-deployed in space / time.

[0027] In an embodiment, the VGL is used to (i) improve SNR, (ii) preserve signal, and (iii) preserve amplitude (eg, extract Q-factor).

[0028] In an embodiment, a method is provided that automatically performs calculations on derivations from user interactions.

[0029] In embodiments, the described method may be used in a variety of applications. In one exemplary embodiment, the method may be used in seismic applications. In another exemplary embodiment, the method may be used in non-seismic applications, such as pipeline integrity assessment and flow assessment.

[0030] In an embodiment, aspects of the present disclosure provide the ability to update the VGL formula according to client requirements regarding resolution loss and HF / LF degradation.

[0031] In embodiments, aspects of the present disclosure provide the ability to perform Q-factor estimation without the need for amplitude compensation due to GL effects.

[0032] In embodiments, aspects of the present disclosure provide for automatic calibration of VGL profiles from acquired VSP data using algorithms to measure the apparent speed and bandwidth of target arrival.

[0033] In embodiments, aspects of the present disclosure provide algorithms that can be traditional signal processing algorithms, inverse problems from physical visco-acoustic modeling, or machine learning based algorithms.

[0034] In embodiments, aspects of the present disclosure provide for multi-offset acquisition, automatic identification of limitations when the current VGL profile is no longer optimal and needs to be recalibrated, instead of constantly calibrating the VGL for each source position.

[0035] In embodiments, aspects of the present disclosure provide for the use of VGL processing for pipeline health monitoring, where VGL allows for mitigating optical loss over length and maintaining a constant detection rate along the entire fiber, while maintaining spatial resolution below the maximum allowable value that would allow intervention.

[0036] In embodiments, aspects of the present disclosure provide for the use of VGL processing to allow flow applications to target the spatial resolution of measurements to their application, for example, higher resolution microseismics requiring lower noise, and lower resolution cluster allocation where closely spaced intervals need to be distinguished.

[0037] Aspects of the present disclosure provide devices and methods that are easier to operate than conventional devices and methods for fiber optic systems.

[0038] Aspects of the present disclosure provide an apparatus and method that does not have the drawbacks discussed above, namely, extensive manual calculations to ensure valid results.

[0039] The economic costs associated with operating optical fiber and its operating equipment for hydrocarbon recovery operations as well as carbon capture and sequestration and geothermal applications are reduced by conventional tools.

[0040] In one exemplary embodiment, a method for processing data is disclosed. The method may include acquiring data from an optical fiber, processing the data using a fixed gauge length, and estimating an apparent velocity using the fixed gauge length with an autonomous computing array. The method may also provide for estimating a source bandwidth from the apparent velocity with the autonomous computing array to generate a result, and establishing a variable gauge length and reference profile of the result. The method may also provide for processing the acquired optical data with the established variable gauge length to obtain a processed optical data set.

[0041] In another exemplary embodiment of the present disclosure, a data processing method may be performed in which data is acquired from in-situ optical fiber at a hydrocarbon recovery project.

[0042] In another exemplary embodiment of the present disclosure, a data processing method may be performed where data is acquired from in-situ optical fiber in a carbon capture and sequestration project.

[0043] In another exemplary embodiment of the present disclosure, a data processing method may be performed in which the acquired optical data is at least one of ZVSP and WAVSP data.

[0044] In another exemplary embodiment of the present disclosure, the data processing method may be performed with a fixed gauge length of 10 meters.

[0045] In another exemplary embodiment of the present disclosure, a data processing method may be performed in which the autonomous computing array is a personal computer.

[0046] In another exemplary embodiment of the present disclosure, a data processing method may be performed in which the autonomous computing array comprises one of a machine learning program and an artificial intelligence program.

[0047] In another exemplary embodiment of the present disclosure, a data processing method may be performed in which a fixed gauge length is predetermined by an operator.

[0048] In another exemplary embodiment of the present disclosure, the data processing method may be performed where the optical fiber is one of a temporarily deployed fiber, a permanently deployed fiber, a downhole deployed optical fiber, a surface deployed optical fiber, and a space / time jointly deployed optical fiber.

[0049] In another exemplary embodiment of the present disclosure, the data processing method may be performed during a hydraulic fracturing project, where the fixed gauge length is greater than 10 meters to ensure low noise levels are generated.

[0050] In another exemplary embodiment of the present disclosure, the data processing method may be performed during a hydraulic fracturing project, where the fixed gauge length is less than 10 meters for targets near the reservoir.

[0051] In another exemplary embodiment of the present disclosure, the data processing method may further include determining a resolution loss of the processed optical dataset, obtaining a desired resolution loss, and comparing the determined resolution loss to the desired resolution loss.

[0052] In another exemplary embodiment of the present disclosure, a data processing method may be performed in which if comparing the determined resolution loss with the desired resolution loss indicates a resolution loss greater than desired, the method is performed a second time.

[0053] In another exemplary embodiment of the present disclosure, the data processing method may further include determining a high frequency loss of the processed optical data set, obtaining a desired high frequency loss, and comparing the high frequency loss to the desired high frequency loss.

[0054] In another exemplary embodiment of the present disclosure, a data processing method may be performed in which if comparing the determined high frequency loss with the desired high frequency loss indicates a high frequency loss that is greater than desired, the method is performed a second time.

[0055] In another exemplary embodiment of the present disclosure, the data processing method may further include determining a low-frequency loss of the processed optical data set, obtaining a desired low-frequency loss, and comparing the low-frequency loss to the desired low-frequency loss.

[0056] In another exemplary embodiment of the present disclosure, a data processing method may be performed in which if comparing the determined low frequency loss with the desired low frequency loss indicates a low frequency loss that is greater than desired, the method is performed a second time.

[0057] In another example, a wellbore method is disclosed that includes deploying optical fiber along well equipment and positioning the well equipment in a wellbore that penetrates a region of interest. The method may also include connecting the optical fiber to a distributed vibration sensing system and utilizing a length of the optical fiber to detect signals indicative of vibrations in the region of interest. The method may further include selecting wavelengths of interest of the detected signals as a function of the length of the optical fiber to generate and apply a variable gauge length profile to phase data obtained from the detected signals, the variable gauge length profile defining a gauge length value that varies as a function of the optical fiber length. The method may also include using the variable gauge length profile to process the phase data obtained from the length of the optical fiber, and processing the phase data obtained from a particular section using a gauge length value associated with a particular section of the optical fiber to generate processed phase data, the variable gauge length being calculated through an autonomous computing system that uses an estimated apparent velocity and an estimated bandwidth of the vibrations.

[0058] The description of the above-described embodiments has been provided for purposes of illustration and description. It is not intended that the disclosure be exhaustive or limiting. Individual elements or features of a particular embodiment are generally not limited to that particular embodiment, but, where applicable, can be interchangeable and used in selected embodiments even if not specifically shown or described. The same may be modified in many ways. Such variations are not considered to be a departure from the disclosure, and all such modifications are intended to be included within the scope of the disclosure.

[0059] While embodiments have been described herein, it will be appreciated by those skilled in the art having the benefit of this disclosure that other embodiments are contemplated that do not depart from the scope of the present invention, and therefore the scope of this or any subsequent claims should not be unduly limited by the description of the embodiments set forth herein.

Claims

1. 1. A data processing method comprising: acquiring data from the optical fiber; processing the data using a fixed gauge length; estimating apparent velocity by an autonomous computing array using said fixed gauge length; estimating a source bandwidth from the apparent speed by the autonomous computing array to generate a result; establishing a variable gauge length and reference profile of the results; processing the acquired data with the established variable gauge length to obtain a processed optical data set; The method comprising:

2. 10. The data processing method of claim 1, wherein the data is obtained from in-situ optical fiber in a hydrocarbon recovery project.

3. 10. The data processing method of claim 1, wherein the data is obtained from in-situ optical fiber in a carbon capture and sequestration project.

4. The data processing method of claim 1 , wherein the acquired optical data is at least one of ZVSP and WAVSP data.

5. 2. The data processing method of claim 1, wherein the fixed gauge length is 10 meters.

6. The method of claim 1 , wherein the autonomous computational array is a personal computer.

7. The method of claim 1 , wherein the autonomous computational array comprises one of a machine learning program and an artificial intelligence program.

8. 2. The data processing method of claim 1, wherein the fixed gauge length is predetermined by an operator.

9. 10. The data processing method of claim 1, wherein the optical fiber is one of a temporarily deployed fiber, a permanently deployed fiber, a downhole deployed optical fiber, a surface deployed optical fiber, and a space / time jointly deployed optical fiber.

10. 10. The method of claim 1, wherein the method is performed during a hydraulic fracturing project and the fixed gauge length is greater than 10 meters to ensure low noise levels are generated.

11. 10. The method of claim 1, wherein the method is performed during a hydraulic fracturing project and the fixed gauge length is less than 10 meters for targets near a reservoir.

12. determining a resolution loss of the processed optical data set; Obtaining a desired resolution loss; comparing the determined resolution loss to the desired resolution loss; The method of claim 1 further comprising:

13. The method of claim 12 , further comprising: performing the method a second time if comparing the determined resolution loss with the desired resolution loss indicates a resolution loss greater than desired.

14. determining a high frequency loss of the processed optical data set; Obtaining a desired high frequency loss; comparing the high frequency loss to the desired high frequency loss; The method of claim 1 further comprising:

15. The method of claim 14 , further comprising: performing the method a second time if comparing the determined high frequency loss to the desired high frequency loss indicates a high frequency loss that is greater than desired.

16. determining a low frequency loss of the processed optical data set; Obtaining a desired low frequency loss; comparing the low frequency loss to the desired low frequency loss; The method of claim 1 further comprising:

17. The method of claim 16 , further comprising: performing the method a second time if comparing the determined low frequency loss to the desired low frequency loss indicates a low frequency loss that is greater than desired.

18. The data processing method of claim 1 , wherein the data is obtained from an optical fiber in communication with a pipeline.

19. 1. A method of use in a well, comprising: deploying optical fiber along the well equipment; positioning the well equipment within a wellbore that penetrates an area of interest; connecting the optical fiber to a distributed vibration sensing system; utilizing the length of optical fiber to detect signals indicative of vibrations within the region of interest; selecting wavelengths of interest in the signal sensed as a function of the length of the optical fiber to generate a variable gauge length profile and applying it to phase data obtained from the sensed signal, the variable gauge length profile defining gauge length values that vary as a function of the optical fiber length; processing the phase data acquired from the length of the optical fiber using the variable gauge length profile, wherein a gauge length value associated with a particular section of a plurality of sections of the optical fiber is used to generate processed phase data by processing the phase data acquired from the particular section, and the variable gauge length is calculated through an autonomous computing system using an estimated apparent velocity of vibration and an estimated bandwidth; The method comprising:

20. 20. The method of claim 19, wherein the phase data is obtained from the length of optical fiber in one of a hydrocarbon recovery project or a carbon capture and sequestration project.

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