Imaging method and processing terminal for borehole distributed optical fiber acoustic vibration monitoring data

Abstract

The present application provides a method for imaging monitoring data of a distributed acoustic sensing (DAS) fiber optic acoustic vibration in a mine shaft and a processing terminal. The imaging method includes steps 1 to 3. In step 1, k segy file data monitored by DAS are preprocessed to obtain a data matrix of size N×M for each segy file. In step 2, for the data matrix of each segy file obtained in step 1, N sample point data within t seconds in each channel of the matrix sample data are taken, and at the same time, the root mean square amplitude calculation is performed on its amplitude while recording the amplitude value. The M amplitude values in each segy file are collected to form each amplitude energy change curve. In step 3, each amplitude energy change curve obtained in step 2 is stacked and arranged in the time order formed by k segy files to form a cross-sectional view of the acoustic vibration energy change in the mine shaft on a long time scale. The present application realizes the imaging of long-period acoustic vibration data in the mine shaft and uses the data monitored by DAS in the mine shaft more efficiently.

Description

[Technical Field]

[0001] The present application relates to the field of well monitoring technology in oil and gas field development, and in particular to an imaging method and processing terminal for well distributed optical fiber acoustic vibration monitoring data. [Background technology]

[0002] Distributed fiber optic acoustic and vibration monitoring systems (DAS) are currently widely used in monitoring illegal excavation in oil and gas pipelines, oil and petrochemical safety, border security, and fiber optic power outage monitoring, with advantages such as long transmission distances, accurate positioning, and continuous distributed surveying. DAS is also currently used to monitor well production status during oil and gas production. Depending on the structure of the well body, optical fiber cables for sensors are sent into the well via pipelines and fully coupled with the well fluid, allowing for monitoring whether sand is coming out of the well, how the fluid is being transported, and the operating status of well production equipment.

[0003] DAS is sensitive to monitoring special phenomena such as fractures in wellbore. The strong acoustic vibration energy generated by fractures is significantly different from the surrounding background acoustic vibration response, allowing DAS monitoring results to be intuitively reflected. However, the acoustic vibration response pattern during multiphase fluid transport in wellbore is unclear, and the resulting acoustic vibration energy is much lower than that of fractures and other activities in wellbore. This makes it difficult to intuitively determine the state of fluid transport in wellbore using raw data monitored by DAS on-site. Multiphase flow status in wellbore is a key indicator for guiding on-site production and plays a very important role. Currently, distributed fiber optic acoustic vibration monitoring systems occupy an irreplaceable position in multiphase flow monitoring in wellbore. However, the relatively complete DAS on the market are produced by relevant foreign manufacturers, and the processing and use of monitoring data is often restricted by foreign service providers. In some cases, data processing can only be performed after production is completed, resulting in poor timeliness.

[0004] During offshore conventional and unconventional oil and gas development, DAS are usually deployed in wells to measure changes in acoustic vibration energy in the well and further guide the production operations in the well. Traditional DAS monitoring can be used to evaluate changes in the working conditions in the well within an instantaneous or short period, such as wellbore fracturing. However, monitoring of long-term unsteady phenomena, such as fluid transport in the well, requires huge data volumes and is severely interfered with by downhole working noise, making it difficult to use for real-time display. Summary of the Invention [Problem to be solved by the invention]

[0005] One of the objectives of this application is to address the deficiencies in the related art by establishing an imaging method and processing terminal for borehole distributed optical fiber acoustic vibration monitoring data. The monitoring data referred to above refers to data passively monitored in a borehole using distributed optical fiber, and is intended to be used to depict long-term production operations such as fluid transport in the borehole. It can accurately process large amounts of DAS data, and the processed DAS data can continuously display micro-vibration phenomena in the borehole while suppressing background noise, thereby achieving rapid imaging with a high signal-to-noise ratio of large amounts of monitoring data. This avoids the disadvantages of traditional DAS monitoring data, which only have a single production monitoring function in the borehole and can only interpret short-period production operations. [Means for solving the problem]

[0006] To achieve the above objectives, the present application adopts the following technical solutions:

[0007] In a first aspect, the present application provides a method for imaging borehole distributed fiber optic acoustic vibration monitoring data, the imaging method including steps 1 to 3: In step 1, the k segy file data monitored by the DAS are preprocessed to obtain a data matrix of size N × M for each segy file. where M is the number of sample data channels, N=t / dt is the total number of sample points in each sample data channel, t is the data recording time, dt is the sampling interval, k is a positive integer, and DAS is a distributed fiber optic acoustic vibration monitoring system. In step 2, for the data matrix of each segy file obtained in step 1, N sample point data within t seconds for each channel of the matrix sample data are taken, and the root mean square amplitude calculation is performed on the amplitude, while each amplitude value is recorded. M amplitude values ​​in each segy file are collected to form one amplitude energy change curve. In step 3, the k amplitude energy change curves obtained in step 2 are stacked and arranged in the order in which the segy files were created to form a cross-sectional view of the change in acoustic vibration energy in the borehole over a long time scale.

[0008] As is clear from the above description of the embodiments, the embodiments of the present application preprocess segy file data to obtain a data matrix, calculate amplitude values ​​from the data matrix, plot and arrange the amplitude values ​​into an energy change curve, obtain a cross-sectional view of the acoustic vibration energy change in the wellbore on a long-time scale, suppress random background noise, improve the signal-to-noise ratio of the entire data, and provide a basis for monitoring long-time-scale unsteady phenomena such as fluid transport in the wellbore.

[0009] In one possible implementation, the root mean square amplitude calculation in step 2 is calculated as follows:

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[0010] Furthermore, calculating the root mean square amplitude value facilitates plotting subsequent amplitude energy variation curves, thereby showing how the downhole acoustic vibration energy varies over time scales.

[0011] In one possible implementation, the preprocessing includes reading channel header information in standard segy format from the raw data, identifying the sampling interval dt, data recording time t, and number of sample data channels M recorded in the channel header based on the channel header information, determining the total number of sample points in each sample data channel as N=t / dt, and obtaining a data matrix of size N×M for each segy file.

[0012] Furthermore, by reading the channel header information of the raw data and obtaining the detailed data of the channel header information, a data matrix is ​​established, which makes it easy to perform subsequent calculations using the data of the data matrix.

[0013] In a second aspect, the present application provides , processing a processing terminal, the processing terminal comprising: a memory for reading and writing stored program instructions in real time; a processor for executing program instructions stored in the memory; The processor executes steps based on a method for imaging downhole distributed fiber optic acoustic and vibratory monitoring data through a parallel algorithm.

[0014] In a third aspect, the present application provides an imaging device for borehole distributed fiber optic acoustic and vibration monitoring data, the imaging device comprising: a preprocessing module for preprocessing k pieces of segy file data monitored by the DAS to obtain an N×M size data matrix for each segy file, where M is the number of sample data channels, N=t / dt is the total number of sample points for each sample data channel, t is the data recording time, dt is the sampling interval, k is a positive integer, and the DAS is a distributed fiber optic acoustic vibration monitoring system; and For the data matrix of each segy file obtained by the preprocessing module, an amplitude acquisition module takes N sample point data within t seconds in each channel of the matrix sample data, performs root mean square amplitude calculation on the amplitude, and records the amplitude value at the same time, collects M amplitude values ​​in each segy file, and forms each amplitude energy change curve; and a cross-sectional view acquisition module for stacking and arranging each amplitude energy change curve acquired by the amplitude acquisition module in the order of time in which the k SEGY files were formed, to form a cross-sectional view of the change in acoustic vibration energy in the borehole over a long time scale.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium having stored thereon computer-executable instructions, which, when executed by a processor, are used to realize the method for imaging borehole distributed fiber optic acoustic vibration monitoring data according to any one of claims 1 to 3. [Effects of the Invention]

[0016] The imaging method and processing terminal for borehole distributed optical fiber acoustic vibration monitoring data provided by the present application have the following beneficial effects:

[0017] (1) Breaking through overseas technology blockades and ensuring data security. Most of the downhole monitoring data in oil and gas development is confidential. If the data is handed over to an overseas service provider for processing, there is a risk of information leaks, which will affect information security. However, by applying a data processing method independently developed through overcoming obstacles, data processing can be highly self-adaptive, resulting in processing results that better meet one's own needs.

[0018] (2) Improves on-site work efficiency and supports on-site engineering decision-making. Data files in the SEGY format take up a large amount of storage space. On-site vibration profiles are often displayed at periods of 30 seconds or shorter on production platforms. The short-term borehole acoustic vibration response cannot intuitively reflect the fluid flow state. Meanwhile, the long-period borehole DAS monitoring data is huge, and post-production processing is a heavy workload. Therefore, the present invention can visualize the long-period borehole acoustic vibration response results using a parallel algorithm without adversely affecting the monitoring quality of the huge amount of data. This compresses the data volume, optimizes data storage space, further improves data processing efficiency, and effectively records the changes in the borehole fluid vibration response. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a flowchart of a method for imaging borehole distributed fiber optic acoustic vibration monitoring data. [Figure 2] FIG. 10 is a diagram of a method for calculating root mean square amplitude of single file data and imaging the data on a long time scale. [Figure 3] Figure (a) shows an example of the original acoustic vibration cross section at a short period, compared with Figure (b) showing an example of the acoustic vibration cross section two months after processing. [Figure 4] 1 is a schematic diagram of a processing terminal provided by an embodiment of the present application; [Figure 5] 1 is a schematic diagram of a downhole distributed fiber optic acoustic vibration monitoring data imaging device provided by an embodiment of the present application. FIG. DETAILED DESCRIPTION OF THE INVENTION

[0020] In order to make the objectives, technical solutions and advantages of the present application clearer and more explicit, the present application will be described in more detail below with reference to the drawings and specific embodiments. It should be understood that the specific examples described in this specification are only used to explain the present application and are not intended to limit the present application. For ease of explanation, the drawings only show parts relevant to the present application, not all of them.

[0021] As shown in Figures 1 to 3, the present application provides a method for imaging well-distributed optical fiber acoustic vibration monitoring data based on data monitored by a DAS regarding micro-vibration responses caused by multiphase flow transport in a well, and the imaging method includes the following steps:

[0022] In step 1, the k segy file data monitored by the DAS are preprocessed to obtain an N × M size data matrix for each segy file. The horizontal direction of the matrix is ​​the increasing direction of the number of channels, and the vertical direction is the increasing direction of time. where M is the number of sample data channels, N=t / dt is the total number of sample points in each sample data channel, t is the data recording time, dt is the sampling interval, k is a positive integer, and DAS is a distributed fiber optic acoustic vibration monitoring system. In step 2, for the data matrix of each segy file obtained in step 1, N sample point data within t seconds for each channel of each matrix sample data are taken, and the amplitude of these sample points is subjected to root mean square amplitude calculation to record one new amplitude value. The M calculated amplitude values ​​in each segy file are collected to form one new amplitude energy change curve. In step 3, the amplitude energy change curves obtained in step 2 are stacked and arranged in the chronological order in which the k SEGY files were formed, thereby compressing and optimizing the huge amount of data and forming a cross-sectional view of the wellbore acoustic vibration energy change over a long time scale. This enables the imaging of the long-period acoustic vibration data of the wellbore and the real-time display of the multi-phase vibration state in the wellbore. The data monitored by the wellbore DAS can be used more efficiently, and the interpretation of the wellbore production operation status can be realized.

[0023] The present application performs accurate processing on a huge amount of DAS data, and the processed DAS data can continuously display the micro-vibration phenomenon of the well in real time. Since the intensity of the background noise caused by the system performance is often lower than the intensity of the actual signal and is random, the present application superimposes a series of actual signals that have a certain regularity within a long period, and then the random background noise is suppressed accordingly, the signal-to-noise ratio of the entire data is improved, and the response characteristics of the fluid transport in the well are revealed, thereby avoiding the shortcomings of traditional DAS monitoring data being mainly used for well fracturing monitoring and opening up new application fields for the monitoring method using DAS systems.

[0024] Preferably, the root mean square amplitude calculation in step 2 is performed using the following formula:

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[0025] Preferably, the preprocessing includes reading channel header information in the standard segy format from the raw data, identifying the sampling interval dt, data recording time t, and number of data sample channels M recorded in the channel header based on the channel header information, determining the total number of sample points in each sample data channel as N=t / dt, and obtaining a data matrix of size N×M for each segy file.

[0026] As shown in Figure 4, the present application , processing a processing terminal, the processing terminal comprising: a memory for reading and writing stored program instructions in real time; a processor for executing program instructions stored in the memory; The processor executes steps based on the imaging method for borehole distributed optical fiber acoustic vibration monitoring data using a parallel algorithm, thereby realizing rapid imaging with a high signal-to-noise ratio for a huge amount of monitoring data, as shown in, for example, FIGS. 1 and 2. Preferably, the program instructions can be divided into one or more modules / units, which are stored in a memory and executed by a processor to complete the present application. One or more modules / units can be a series of program instruction segments capable of achieving a specific function, which is used to describe the execution process of the program instructions in a processing terminal. Preferably, the processing terminal can be a computing device such as a desktop computer, a laptop computer, a handheld computer, or a cloud server. The processing terminal can include, but is not limited to, a processor and a memory.

[0027] This application divides a huge amount of monitoring data by time and performs root mean square averaging on the short-period data, thereby effectively compressing the data volume without adversely affecting data quality, enabling continuous display of DAS data over long time scales and suppressing random noise in the system. This noise is characterized by small amplitude but irregularity, and by using the root mean square superposition method described above, the random noise is further suppressed. Furthermore, the data processing method is simple and computationally efficient, allowing it to be directly used as an independent module of on-site data processing and visualization software. This solves the problem of the original DAS data not providing clear indications of long-period production operation conditions related to on-site fluid transport, etc., and provides important data guidance for on-site conventional and unconventional oil and gas drilling activities, further clarifying the operating conditions of the produced fluid in the well. Most of the downhole monitoring data in oil and natural gas development is confidential, so if the data is handed over to an overseas service provider for processing, there is a risk of information leaks, which affects information security. However, if a data processing method developed through independent oversight is applied, the data processing is highly self-adaptive, resulting in processing results that better meet one's own needs and ensuring data security.

[0028] It should be noted that the number of time sample points of the acoustic vibration energy change cross section finally formed in this specification is the same as the number of SEGY files formed by collection, and the time interval of the data display becomes larger. However, in the case of long-term continuous monitoring data with a cycle of months or years, the impact of changing the sampling time interval unit from milliseconds to seconds can be ignored. Furthermore, this processing method significantly reduces the data storage space and does not affect the display of the overall work situation.

[0029] 5 is a schematic diagram of a borehole distributed optical fiber acoustic vibration monitoring data imaging device provided by an embodiment of the present application. As shown in FIG. 5, the borehole distributed optical fiber acoustic vibration monitoring data imaging device 500 includes a pre-processing module 501, an amplitude acquisition module 502, and a cross-sectional view acquisition module 503.

[0030] The pre-processing module 501 is used to pre-process the k segy file data monitored by the DAS to obtain an N×M size data matrix for each segy file, where M is the number of sample data channels, N=t / dt is the total number of sample points for each sample data channel, t is the data recording time, dt is the sampling interval, k is a positive integer, and DAS is a distributed optical fiber acoustic vibration monitoring system; The amplitude acquisition module 502 acquires N sample point data within t seconds for each channel of the matrix sample data for each segy file data matrix acquired by the pre-processing module, performs root mean square amplitude calculation on the amplitude, and records the amplitude value at the same time, collects M amplitude values ​​in each segy file, and uses them to form each amplitude energy change curve; The cross-sectional view acquisition module 503 is used to stack and arrange each amplitude energy change curve acquired by the amplitude acquisition module in the time order in which the k segy files were created, to form a cross-sectional view of the change in acoustic vibration energy in the borehole over a long time scale.

[0031] The device provided by this embodiment can be used to implement the technical solutions according to the above method embodiments, and the realization principles and technical effects are similar, so this embodiment will not be described again here.

[0032] In one possible implementation, the amplitude acquisition module 502 performs a root mean square amplitude calculation as follows:

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[0033] The device provided by this embodiment can be used to implement the technical solutions according to the above method embodiments, and the realization principles and technical effects are similar, so this embodiment will not be described again here.

[0034] In one possible implementation, the pre-processing module 501 reads channel header information in standard segy format from the raw data, and based on the channel header information, identifies the sampling interval dt, data recording time t, and number of sample data channels M recorded in the channel header, determines the number of sample points for each sample data channel as N=t / dt, and is used to obtain a data matrix of size N×M for each segy file.

[0035] The device provided by this embodiment can be used to implement the technical solutions according to the above method embodiments, and the realization principles and technical effects are similar, so this embodiment will not be described again here.

[0036] The present application further provides a computer-readable storage medium, which stores computer-executable instructions. When a processor executes the computer-executable instructions, the technical solution related to the imaging method for borehole distributed optical fiber acoustic vibration monitoring data in any one of the above embodiments is realized, and its realization principle and beneficial effects are similar to those of the imaging method for borehole distributed optical fiber acoustic vibration monitoring data, so reference can be made to the realization principle and beneficial effects of the imaging method for borehole distributed optical fiber acoustic vibration monitoring data, and they will not be repeated here.

[0037] The above description merely describes the preferred embodiments and applied technical principles of the present application. Those skilled in the art should understand that the scope of the present application is not limited to the technical solution consisting of a specific combination of the above technical features, and also includes other technical solutions consisting of any combination of the above technical features or their equivalent features without departing from the concept described above. For example, the above features may be substituted with technical features having similar functions (including but not limited to) described in the present application.

[0038] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention described herein. This application is intended to cover any variations, uses, or adaptations of the present application, including common knowledge or customary technical means in the art, in accordance with the general principles of the present application, but not described herein. The specification and examples are considered to be exemplary only, with the true scope and spirit of the present application being indicated by the following claims.

[0039] The above examples are only intended to explain the technical concepts and features of the present application, and are intended to enable those skilled in the art to understand and implement the content of the present application, and do not limit the scope of protection of the present application. Any equivalent changes or modifications made based on the essence of the content of the present application shall be included in the scope of protection of the present application.

[0040] This application claims priority to a Chinese patent application bearing application number 2023107428688 and entitled "Imaging method and processing terminal for borehole distributed optical fiber acoustic vibration monitoring data," filed with the China Patent Office on June 21, 2023, the entire contents of which are incorporated herein by reference.

Claims

1. A method for imaging borehole distributed fiber optic acoustic vibration monitoring data, comprising steps 1, 2 and 3: In step 1, the k SEGY file data monitored by the DAS are preprocessed to obtain an N×M size data matrix for each SEGY file; where M is the number of sample data channels, N=t / dt is the total number of sample points in each sample data channel, t is the data recording time, dt is the sampling interval, k is a positive integer, DAS is a distributed fiber optic acoustic vibration monitoring system, In step 2, for the data matrix of each SEGY file acquired in step 1, N sample point data within t seconds in each channel of the matrix sample data are taken, and the root mean square amplitude calculation is performed on the amplitude and the amplitude value is recorded at the same time. M amplitude values ​​in each SEGY file are collected to form each amplitude energy change curve, and the root mean square amplitude calculation is performed using the following formula: [Equation 1] where: [Equation 2] is the root mean square amplitude value of the mth channel, n is the sequence of sample point data in each channel, [Equation 3] is the amplitude value of the nth sample point within t seconds of the mth channel, M is the number of sample data channels, N=t / dt is the total number of sample points of each sample data channel, t is the data recording time, and dt is the sampling interval; In step 3, the amplitude energy change curves obtained in step 2 are stacked and arranged in the time order in which the k SEGY files were created, to form a cross-sectional view of the change in acoustic vibration energy in the borehole over a long-term scale. This is a method for imaging borehole distributed optical fiber acoustic vibration monitoring data.

2. The method for imaging borehole distributed optical fiber acoustic vibration monitoring data described in claim 1, characterized in that the preprocessing includes reading channel header information in the standard SEGY format from the raw data, identifying the sampling interval dt, data recording time t, and number of sample data channels M recorded in the channel header based on the channel header information, determining the number of sample points for each sample data channel as N = t / dt, and obtaining an N x M size data matrix for each SEGY file.

3. a memory for reading and writing stored program instructions in real time; a processor for executing program instructions stored in said memory, 10. A processing terminal, wherein the processor executes the steps of the method for imaging borehole distributed fiber optic acoustic vibration monitoring data according to claim 1 using a parallel algorithm.

4. a pre-processing module for pre-processing k segly file data monitored by the DAS to obtain an N×M size data matrix for each segly file, where M is the number of sample data channels, N=t / dt is the total number of sample points for each sample data channel, t is the data recording time, dt is the sampling interval, k is a positive integer, and the DAS is a distributed fiber optic sound and vibration monitoring system; and An amplitude acquisition module for acquiring N sample point data within t seconds for each channel of the matrix sample data for each data matrix of each SEGY file acquired by the pre-processing module, performing root mean square amplitude calculation on the amplitude and recording the amplitude value, and collecting M amplitude values ​​in each SEGY file to form each amplitude energy change curve; and a cross-sectional view acquisition module for stacking and arranging each amplitude energy change curve acquired by the amplitude acquisition module in the order of time when the k SEGY files were formed, to form a cross-sectional view of the change in acoustic vibration energy in the borehole on a long-time scale; The root mean square amplitude calculation is performed using the following formula: [Equation 4] where: [Equation 5] is the root mean square amplitude value of the mth channel, n is the sequence of sample point data in each channel, [Equation 6] is the amplitude value of the nth sample point within t seconds of the mth channel, M is the number of sample data channels, N = t / dt is the total number of sample points of each sample data channel, t is the data recording time, and dt is the sampling interval.

5. 10. A computer-readable storage medium having stored thereon computer-executable instructions, the computer-executable instructions, when executed by a processor, being used to implement the method for imaging borehole distributed fiber optic acoustic vibration monitoring data of claim 1.

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