CN117333575B - Shaft distributed optical fiber acoustic vibration monitoring data imaging method and processing terminal - Google Patents

Abstract

The invention provides a method for imaging wellbore distributed optical fiber acoustic vibration monitoring data and a processing terminal, which comprise the following steps: step one, preprocessing k segy file data monitored by a DAS (data acquisition system) to obtain a data matrix of each segy file, wherein the size of the data matrix is N multiplied by M; step two, the data matrix of each segy file obtained in the step one is obtained, N sample point data in t seconds in each track of matrix sample data are taken, the amplitude of the sample point data is subjected to root mean square calculation, amplitude values are recorded, and M amplitude values in each segy file are collected to form each amplitude energy change curve; and thirdly, superposing and arranging each amplitude energy change curve obtained in the second step according to the time sequence formed by k segy files to form a section view of acoustic vibration energy change in the shaft under a long time scale. The invention realizes imaging of long-period acoustic vibration data of the well bore, and makes more efficient use of data monitored by DAS of the well bore.

Description

A wellbore distributed optical fiber acoustic vibration monitoring data imaging method and processing terminal

Technical Field

The invention relates to the technical field of wellbore monitoring for oil and gas field development, and in particular to a wellbore distributed optical fiber acoustic vibration monitoring data imaging method and a processing terminal.

Background technique

Distributed fiber acoustic vibration monitoring system (DAS) is now widely used in monitoring illegal excavation of oil and gas pipelines, petroleum and petrochemical security, border security, fiber power failure monitoring, etc. It has the advantages of long transmission distance, accurate positioning, and continuous distributed measurement. DAS is also used in the wellbore production status monitoring during the oil and gas production process. According to the wellbore structure, the sensor optical cable is sent into the wellbore through the oil pipe and fully coupled with the wellbore fluid. It can monitor whether sand is produced in the well, how the fluid moves, and the activity status of the wellbore production tools.

DAS is more sensitive to special phenomena such as fracturing activities in monitoring wells, because the acoustic vibration energy generated by fracturing is strong and there is a significant difference with the surrounding background acoustic vibration response, which can be reflected more intuitively in the DAS monitoring results. However, the acoustic vibration response law of wellbore multiphase fluid migration is not clear, and the acoustic vibration energy caused by it is much lower than that of downhole fracturing and other such activities. The original data of DAS on-site monitoring cannot intuitively judge the fluid migration state in the well. The migration state of wellbore multiphase flow is one of the important indicators to guide on-site production, and it has a very important position. At this stage, the distributed optical fiber acoustic vibration monitoring system has an irreplaceable position in wellbore multiphase flow monitoring, but the more mature DAS on the market are all produced by relevant foreign manufacturers. The processing and application of monitoring data are often subject to the restrictions of foreign service providers. Some need to be processed after the production results, which has low timeliness.

In the process of conventional and unconventional offshore oil and gas development, DAS is usually deployed in the wellbore to realize the change of acoustic vibration energy in the wellbore and further indicate the downhole production activities. Conventional DAS monitoring can be used to evaluate the instantaneous or short-term operating condition changes in the wellbore, such as wellbore fracturing, but for the monitoring of long-term non-steady-state phenomena such as fluid migration in the wellbore, there is still a lack of real-time display applications due to the large amount of data and serious interference from wellbore industrial noise in the data signal.

Summary of the invention

In view of the deficiencies in the prior art, one of the purposes of the present invention is to establish a wellbore distributed optical fiber acoustic vibration monitoring data imaging method and processing terminal. The monitoring data referred to is the data of passive monitoring in the wellbore using distributed optical fiber. The purpose is to serve the characterization of long-term production activities such as wellbore fluid migration. Massive DAS data can be processed in a targeted manner. The processed DAS data can realize the continuous display of wellbore micro-vibration phenomena, while suppressing background noise, and can achieve high signal-to-noise ratio rapid imaging of massive monitoring data, thereby avoiding the shortcomings of existing DAS monitoring data in underground production monitoring with a single function and only being able to explain short-term production activities.

In order to achieve the above objectives, the technical solution adopted by the present invention is:

The present invention provides a wellbore distributed optical fiber acoustic vibration monitoring data imaging method, comprising the following steps:

Step 1: pre-process the k segy file data monitored by the DAS to obtain a data matrix of each segy file, where the size of the data matrix is N×M;

Wherein, 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 optical fiber acoustic vibration monitoring system;

Step 2: for each segy file data matrix obtained in step 1, take N sample point data within t seconds in each channel of matrix sample data, calculate the root mean square amplitude of the amplitude and record each amplitude value, and aggregate the M amplitude values in each segy file to form each amplitude energy change curve;

Step 3: The k amplitude energy change curves obtained in step 2 are superimposed and arranged in the time sequence of the formation of the segy file to form a cross-sectional diagram of the acoustic vibration energy change in the wellbore on a long time scale.

Furthermore, the root mean square amplitude calculation in step 2 is calculated as follows:

Wherein, _AM is the RMS amplitude value of the mth channel, n is the sequence of sample data in each channel, A _mn is the amplitude value of the nth sample 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 in each sample data channel, t is the data recording time, and dt is the sampling interval.

Furthermore, the preprocessing includes: reading the header information in the standard segy format in the original data, and based on the header information, identifying the sampling interval dt, data recording time t, and the number of sample data tracks M recorded in the header, and determining that the total number of sample points in each sample data track is N=t/dt, so as to obtain the data matrix of each segy file, and the size of the data matrix is N×M.

The present invention provides a real-time processing terminal, comprising:

Memory, used to read and write stored program instructions in real time;

A processor, configured to execute program instructions stored in the memory;

The processor uses a parallel algorithm to execute steps based on a wellbore distributed optical fiber acoustic vibration monitoring data imaging method.

The beneficial effects of the present invention are:

(1) Protect data security.

(2) Improve on-site work efficiency and support on-site engineering decision-making. Since the segy format data file occupies a large storage space, the production platform site is often displayed as a vibration state profile according to a period of 30s or less. The acoustic vibration response in the wellbore in a short period of time cannot intuitively reflect the state of fluid migration. At the same time, the long-period wellbore DAS monitoring data is massive data, but the processing work after the production is completed is arduous. The use of the present invention can be based on a parallel algorithm to describe the long-period wellbore acoustic vibration response results without affecting the monitoring quality, compress the data volume, optimize the data storage space, further improve the data processing efficiency, and effectively record the changes in the wellbore fluid vibration response.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a method for imaging wellbore distributed optical fiber acoustic vibration monitoring data;

Fig. 2 is a diagram showing the calculation of the root mean square amplitude of single file data and the data imaging method at a long time scale;

FIG3 is a comparison diagram of an original acoustic vibration profile example within a short period in FIG(a) and an acoustic vibration profile example within 2 months after processing in FIG(b);

FIG. 4 is a schematic diagram of a processing terminal provided in an embodiment of the present application.

Detailed ways

In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the content of the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It is understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for the convenience of description, only the parts related to the present invention are shown in the accompanying drawings, rather than all the contents.

As shown in FIGS. 1 to 3 , in view of the micro-vibration response caused by the migration of multiphase flow in the wellbore, combined with the data monitored by DAS, the present invention provides a wellbore distributed optical fiber acoustic vibration monitoring data imaging method, comprising the following steps:

The present invention provides a wellbore distributed optical fiber acoustic vibration monitoring data imaging method, comprising the following steps:

Step 1: pre-process the k segy file data monitored by DAS to obtain a data matrix of each segy file, wherein the size of the data matrix is N×M, 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;

Wherein, 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 optical fiber acoustic vibration monitoring system;

Step 2: for each segy file data matrix obtained in step 1, take N sample point data within t seconds in each matrix sample data, perform RMS calculation on the amplitude of these sample points and record them as a new amplitude value, and aggregate the M calculated amplitude values in each segy file to form a new amplitude energy change curve;

Step three, each amplitude energy change curve obtained in the step two is superimposed and arranged in the time sequence formed by k segy files, so as to achieve compression and optimization of massive data, so as to form a wellbore acoustic vibration energy change profile on a long time scale, thereby realizing imaging of the long-period acoustic vibration data of the wellbore; at the same time, the real-time display of the multi-phase vibration state of the wellbore can be realized, so that the data monitored by the wellbore DAS can be used more efficiently, thereby realizing the interpretation of the production conditions in the wellbore.

The present invention processes massive amounts of DAS data in a targeted manner. The processed DAS data can continuously display micro-vibration phenomena in the wellbore in real time. The intensity of background noise caused by system performance is often lower than the intensity of actual signals and is random. After superimposing a batch of real signals with certain regularity in a long period, the present invention suppresses the random background noise accordingly, thereby improving the overall signal-to-noise ratio of the data. By identifying the response characteristics of wellbore fluid migration, the shortcoming of existing DAS monitoring data being mainly used for wellbore fracturing monitoring is avoided, thus opening up a new application field for the DAS system monitoring method.

Preferably, the calculation formula for the root mean square amplitude calculation in step 2 is:

Wherein, _AM is the RMS amplitude value of the mth channel, n is the sequence of sample data in each channel, A _mn is the amplitude value of the nth sample 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 in each sample data channel, t is the data recording time, and dt is the sampling interval.

Preferably, the preprocessing includes: reading the header information in the standard segy format in the original data, and based on the header information, identifying the sampling interval dt, data recording time t, and the number of data sample tracks M recorded in the header, and determining that the total number of sample points in each sample data track is N=t/dt, so as to obtain the data matrix of each segy file, wherein the size of the data matrix is N×M.

As shown in FIG4 , the present invention provides a real-time processing terminal, comprising:

Memory, used to read and write stored program instructions in real time;

A processor, configured to execute program instructions stored in the memory;

Wherein, the processor uses a parallel algorithm to execute the steps based on a wellbore distributed optical fiber acoustic vibration monitoring data imaging method, such as shown in Figures 1 and 2, which can achieve high signal-to-noise ratio rapid imaging of massive monitoring data. Preferably, the program instructions can be divided into one or more modules/units, and the one or more modules/units are stored in the memory and executed by the processor to complete the present invention. The one or more modules/units can be a series of program instruction segments that can perform specific functions, and the instruction segments are used to describe the execution process of the program instructions in the processing terminal. Preferably, the processing terminal can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The processing terminal may include, but is not limited to, a processor and a memory.

The present invention divides the massive monitoring data by time and performs root mean square averaging on the data in a short period, thereby effectively compressing the data volume without affecting the data quality, and realizing continuous display of DAS data in a long time scale. In addition, the present invention also realizes the suppression of random interference noise of the system, which is characterized by a small amplitude of the noise but no regularity. The suppression method is the root mean square superposition mentioned above, so that the random noise is further suppressed; the data calculation and processing method is simple and has high calculation efficiency, and can be directly used as an independent module in the field data processing and imaging software, so as to solve the problem that the original DAS data cannot clearly indicate the production conditions of the long period scale related to the field fluid migration, etc., and provides important data guidance for the field conventional oil and gas and unconventional oil and gas production activities, and further clarifies the activity state of the production fluid in the wellbore.

It should be noted that the number of time sample points of the acoustic vibration energy change profile finally formed here is consistent with the number of segy files formed by the acquisition. Although the time interval of the data display becomes larger, for long-term continuous monitoring data with a period of months or years, the impact of changing the sampling time interval unit from milliseconds to seconds is negligible. In addition, this processing method greatly compresses the data storage space and will not affect the display of the overall working conditions.

The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable ordinary technicians in the field to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made based on the essence of the content of the present invention should be included in the protection scope of the present invention.

Claims (3)

1. A method for imaging wellbore distributed optical fiber acoustic vibration monitoring data, characterized in that it comprises the following steps: Step 1: pre-process the k segy file data monitored by the DAS to obtain a data matrix of each segy file, where the size of the data matrix is N×M; Wherein, 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 optical fiber acoustic vibration monitoring system; Step 2: For each segy file data matrix obtained in step 1, take N sample point data within t seconds in each channel of matrix sample data, perform RMS calculation on its amplitude and record the amplitude value, and collect the M amplitude values in each segy file to form each amplitude energy change curve; wherein, the RMS calculation of its amplitude is calculated by the following formula: in, is the RMS amplitude of the mth channel, n is the sequence of sample data in each channel, /> is the amplitude value of the nth sample point in t seconds of the mth channel, 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, and dt is the sampling interval; Step 3: Each amplitude energy change curve obtained in step 2 is superimposed and arranged in the time sequence of the k segy files to form a cross-sectional diagram of the acoustic vibration energy change in the wellbore on a long time scale. 2. The method for imaging data of wellbore distributed optical fiber acoustic vibration monitoring according to claim 1 is characterized in that: the preprocessing includes: reading the header information of the standard segy format in the original data, based on the header information, identifying the sampling interval dt, data recording time t, and the number of sample data tracks M recorded in the header, and determining the number of sample points of each sample data track as N=t/dt, so as to obtain the data matrix of each segy file, and the size of the data matrix is N×M. 3. A real-time processing terminal, comprising: Memory, used to read and write stored program instructions in real time; A processor, configured to execute program instructions stored in the memory; The processor executes the steps of the wellbore distributed optical fiber acoustic vibration monitoring data imaging method according to any one of claims 1 to 2 through a parallel algorithm.