Submarine co2 storage induced fault activation microseismic monitoring system and identification method

Abstract

The application provides a seabed CO2 storage induced fault activation microseismic monitoring system and identification method, the method comprising: obtaining a data signal in a seabed CO2 injection process; calculating the distance between a monitoring position and a seismic source based on the data signal to locate the seismic source position; obtaining a seismic source moment tensor and a moment magnitude based on the seismic source position, and obtaining a seismic source mechanism solution based on the seismic source moment tensor; taking the seismic source mechanism solution as a clustering parameter, and performing spatial clustering analysis on all microseismic events in the seabed CO2 injection process to obtain a potential blind fault corresponding to each cluster; performing a magnitude-frequency nonlinear fitting based on the moment magnitude on all microseismic events on each potential blind fault to obtain a seismic b value of seismic activity on a fault surface, and identifying fault activation based on the seismic b value. The application can realize real-time monitoring of the fault state in seabed CO2 geological storage and identify possible fault activation.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of marine CO2 geological storage, and particularly relates to the field of microseismic monitoring and identification of fault activation induced by submarine CO2 storage. BACKGROUND

[0002] Carbon capture, utilization and storage (CCUS) is a necessary technical means to achieve the "double carbon" goal, and carbon geological utilization and storage (CGUS) is a key link of CCUS technology, that is, the process of injecting CO2 captured by industry into deep saline aquifers, depleted oil and gas fields and other geological bodies to achieve permanent reduction of CO2. Marine CO2 geological storage has huge storage potential compared to onshore storage, and is the future development trend of CCUS.

[0003] However, large-scale CO2 injection can significantly change the state of the formation and bring various geological and environmental risks. Among them, as the weak link of the geological structure of the formation, the fault has the risk of activation due to stress changes caused by CO2 injection. Although large faults are avoided as much as possible during the engineering site selection stage of CO2 geological storage, a large number of small faults are still difficult to avoid. Fault activation caused by CO2 injection may damage the sealing of faults, caprocks and wellbores, increase the risk of CO2 leakage, and even may induce geological disasters such as earthquakes and landslides. Therefore, monitoring and identification of fault activation are of great significance to the safety of submarine CO2 geological storage.

[0004] At present, for the development of shallow resources of the submarine, such as hydrate exploitation and metal mine exploitation, the cross-section stress and transverse deformation of the anchor rod passing through the fault can be monitored by using strain gauges and displacement meters to obtain the stress and displacement changes of the fault, so as to identify the fault activation. However, for submarine CO2 geological storage such as saline aquifer storage and oil displacement storage, the depth of the storage target reservoir often reaches 2000-3000m, and there may be hidden faults that are difficult to locate accurately. The method of monitoring fault activation by anchor rod deformation is no longer applicable. SUMMARY

[0005] The application provides a submarine CO2 storage induced fault activation microseismic monitoring system and identification method to realize real-time monitoring of the state of the fault in submarine CO2 geological storage and identification of possible fault activation.

[0006] In a first aspect, the embodiments of the present application provide a seabed CO2 storage induced fault activation microseismic monitoring system, comprising: a downhole optical fiber and a downhole signal acquisition unit located in a monitoring well, a seabed optical fiber and a seabed signal acquisition unit located on the seabed of the seabed centering on an injection well, a control unit, a distribution unit, a signal conversion unit and a wireless transmission unit located on the offshore platform of the injection well, a wireless receiving unit and a data analysis unit located in a monitoring center; the downhole optical fiber is used to pick up the microseismic signals propagating to the monitoring well; the downhole signal acquisition unit is used to acquire the microseismic signals of the monitoring well picked up by the downhole optical fiber; the seabed optical fiber is used to pick up the microseismic signals propagating to the seabed surface; the seabed signal acquisition unit is used to acquire the microseismic signals of the seabed surface picked up by the seabed optical fiber; the control unit is used to power the distribution unit, GPS positioning and time calibration of the downhole signal acquisition unit and the seabed signal acquisition unit, acquisition of microseismic acquisition positioning data and timing data, and transmission of the acquired microseismic acquisition positioning data and timing data to the wireless transmission unit; the distribution unit is used to distribute optical signals to the downhole optical fiber and the seabed optical fiber, and to transmit the combined microseismic signals returned by the downhole optical fiber and the seabed optical fiber to the signal conversion unit; the signal conversion unit converts the combined microseismic signals into data signals and sends them to the wireless transmission unit; the wireless transmission unit wirelessly transmits the received data signals to the wireless receiving unit located in the monitoring center; the wireless receiving unit transmits the received data signals to the data analysis unit; the data analysis unit analyzes the data signals, and monitors and identifies the activation of the fault in real time.

[0007] In a second aspect, the embodiments of the present application provide a method for identifying seabed CO2 storage induced fault activation, wherein a seabed CO2 storage induced fault activation microseismic monitoring system is arranged in a monitoring area, the method comprising: acquiring data signals during seabed CO2 injection; calculating the distance between the monitoring position and the seismic source based on the data signals to locate the seismic source position; obtaining the seismic source moment tensor and the moment magnitude based on the seismic source position, and obtaining the seismic source mechanism solution based on the seismic source moment tensor; taking the seismic source mechanism solution as a clustering parameter, performing spatial clustering analysis on all microseismic events during seabed CO2 injection, and obtaining a potential blind fault corresponding to each cluster; based on the moment magnitude, performing linear fitting on the magnitude-frequency of all microseismic events on each potential blind fault to obtain the seismic b value of the seismic activity on the fault plane, and identifying the fault activation based on the seismic b value.

[0008] In an embodiment of the second aspect, the influence range of the microseismic monitoring of the seabed CO2 geological storage is estimated by using an analytical solution model of the reservoir fluid pressure in CO2 geological storage, and the monitoring area is determined based on the influence range; wherein the influence range includes a CO2 enrichment zone, a CO2 plume front transition zone, and a CO2 pressure influence zone; a monitoring well is arranged in the annular range of the CO2 plume front transition zone, and a distributed downhole optical fiber is arranged in the monitoring well to a certain depth of the upper reservoir; an injection well is arranged in the center of the CO2 enrichment zone, and a plurality of distributed seabed optical fibers are arranged in a uniform radial manner on the seabed surface with the injection well as the center; a control unit, a distribution unit, a signal conversion unit, and a wireless transmission unit are arranged on the offshore platform of the injection well, and a wireless receiving unit and a data analysis unit are arranged in the offshore monitoring center or onshore.

[0009] In an embodiment of the second aspect, in the process of obtaining the data signal in the seabed CO2 injection, the abnormal microseismic signal is also judged and removed; wherein the abnormal microseismic signal is judged by the Pearson correlation coefficient between the waveforms between different monitoring positions.

[0010] In an embodiment of the second aspect, the calculation of the distance between the monitoring position and the seismic source based on the data signal includes: using the long-short time window energy ratio method to pick up the first arrival of the waveform of each monitoring position; obtaining the arrival time difference between P wave and S wave and the wave velocity of P wave and S wave according to the waveform of the monitoring position; and calculating the distance between the monitoring position and the seismic source according to the arrival time difference between P wave and S wave and the wave velocity of P wave and S wave.

[0011] In an embodiment of the second aspect, the optimal seismic source position is obtained by using ray tracing combined with arithmetic optimization algorithm.

[0012] In an embodiment of the second aspect, the seismic moment tensor is obtained based on the seismic source position, and the calculation of the moment magnitude and the seismic source mechanism solution based on the seismic moment tensor includes: obtaining the amplitudes of P wave and S wave at the monitoring position based on the seismic source position; obtaining the amplitude vector w of P wave and S wave at the monitoring position, and obtaining the seismic moment tensor M inversion vector based on the amplitude vector w. G is an overdetermined matrix; the inversion vector The normalized seismic source mechanism solution is determined.

[0013] In an embodiment of the second aspect, it also includes: decomposing the eigenvalues of the normalized seismic source mechanism solution to obtain the isotropic source tensor, the compensated linear vector source tensor, and the double couple source tensor; and drawing the seismic source mechanism beach ball of all microseismic events based on the isotropic source tensor, the compensated linear vector source tensor, and the double couple source tensor.

[0014] In an implementation form of the second aspect, the minimum number k of microseismic events in a cluster is: where m is the number of microseismic events.

[0015] In an implementation form of the second aspect, when the seismic b value is less than or equal to 1, it is determined that the fault enters an activation stage.

[0016] The method for identifying fault activation induced by seabed CO2 storage provided by the embodiments has the following beneficial effects:

[0017] 1. The method comprehensively uses downhole monitoring and seabed monitoring means, improves the redundancy of the monitoring system, makes the positioning of the seismic source more accurate, can realize real-time monitoring of the fault state in seabed CO2 geological storage, and can identify possible fault activation.

[0018] 2. The method estimates the monitoring range in advance according to the actual seabed CO2 geological storage project, so that the arrangement of the monitoring facilities is more reasonable and targeted.

[0019] 3. The method performs cluster analysis on all microseismic events in the CO2 injection process, and has the ability to identify potential blind faults.

[0020] 4. The method identifies fault activation according to the b value of seismic activity on the fault plane, and can predict the tectonic activity of the fault in advance before a large-magnitude earthquake occurs. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 FIG. 1 shows a basic structure schematic diagram of a microseismic monitoring system for identifying fault activation induced by seabed CO2 storage according to an embodiment of the present application.

[0022] Figure 2 FIG. 2 shows a whole flowchart of a method for identifying fault activation induced by seabed CO2 storage according to an embodiment of the present application.

[0023] Figure 3 FIG. 3 shows a schematic diagram of monitoring range estimation and monitoring facility arrangement in a method for identifying fault activation induced by seabed CO2 storage according to an embodiment of the present application.

[0024] Figure 4 FIG. 4 shows a schematic diagram of identifying fault activation induced by seabed CO2 storage by using a microseismic monitoring system according to an embodiment of the present application.

[0025] Figure 5 FIG. 5 shows a flowchart of determining a seismic source position in a method for identifying fault activation induced by seabed CO2 storage according to an embodiment of the present application.

[0026] Figure 6The figure shows an example of the source location, source mechanism inversion and source clustering analysis in the method for identifying the seabed CO2 storage-induced fault activation according to an embodiment of the present application.

[0027] Figure 7 The figure shows the magnitude-frequency G-R relationship fitting of the seismic activity on a certain fault and the corresponding b value map in the method for identifying the seabed CO2 storage-induced fault activation according to an embodiment of the present application.

[0028] Element number explanation

[0029] 100 seabed CO2 storage-induced fault activation microseismic monitoring system

[0030] 110 downhole optical fiber

[0031] 120 seabed optical fiber

[0032] 130 downhole signal acquisition unit

[0033] 140 seabed signal acquisition unit

[0034] 150 control unit

[0035] 160 distribution unit

[0036] 170 signal conversion unit

[0037] 180 wireless transmitting unit

[0038] 190 wireless receiving unit

[0039] 1110 data analysis unit

[0040] 10 injection well

[0041] 20 monitoring well

[0042] 30 offshore platform

[0043] 40 CO2 plume front transition zone

[0044] 50 fault

[0045] 60 reservoir

[0046] S100-S500 steps

[0047] S210-S230 steps DETAILED DESCRIPTION

[0048] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed according to different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0049] This application provides a microseismic monitoring system and identification method for fault activation induced by seabed CO2 sequestration, so as to realize real-time monitoring of fault status in seabed CO2 geological sequestration and identify possible fault activation.

[0050] The method for identifying fault activation induced by CO2 seismic activity induced by seabed seismic activity provided in this application embodiment can estimate the monitoring range and reasonably arrange monitoring equipment. After initializing the monitoring system, microseismic signals are collected by joint monitoring of downhole optical fiber and seabed optical fiber and transmitted to the data analysis unit for preprocessing via wireless communication. After first arrival picking using the long-short time window energy ratio method, the microseismic events are accurately located by ray tracing combined with optimization algorithms. Potential hidden faults are accurately identified by source mechanism inversion based on amplitude information and source clustering analysis based on density. Finally, fault activation is identified based on the b-value of seismic activity on the fault plane.

[0051] The following will refer to the appendices in the embodiments of this application. Figure 1 To be continued Figure 7 This application provides a detailed description of the technical solutions in its embodiments. This allows those skilled in the art to understand and implement the microseismic monitoring system and identification method for seabed CO2 seismic induced fault activation without inventive effort.

[0052] This application provides a microseismic monitoring system for fault activation induced by seabed CO2 seismic storage. Figure 1 The diagram shown is a basic structural schematic of a microseismic monitoring system for seabed CO2 seismic storage-induced fault activation, according to an embodiment of this application. Figure 1 As shown, the microseismic monitoring system 100 for seabed CO2 seismic induced fault activation in this embodiment includes: a downhole optical fiber 110 and a downhole signal acquisition unit 130 located in the monitoring well 20; a seabed optical fiber 120 and a seabed signal acquisition unit 140 located on the seabed centered on the injection well 10; a control unit 150, a distribution unit 160, a signal conversion unit 170, and a wireless transmission unit 180 located on the offshore platform 30 of the injection well 10; and a wireless receiving unit 190 and a data analysis unit 1110 located at the monitoring center.

[0053] The optical signal is distributed to the downhole optical fiber 110 and the submarine optical fiber 120 by the distribution unit 160, and the microseismic-induced optical signal is collected by the downhole signal collection unit 130 and the submarine signal collection unit 140, converted into a data signal by the signal conversion unit 170, and wirelessly transmitted by the wireless transmission unit 180 and the wireless reception unit 190, and finally analyzed and processed by the data analysis unit 1110, so as to monitor and identify the state of the fault 50 in real time.

[0054] The submarine CO2 storage-induced fault activation microseismic monitoring system 100 of the present embodiment will be described in detail below.

[0055] In the present embodiment, the downhole optical fiber 110 is used to pick up the microseismic signal propagating to the monitoring well 20. The downhole optical fiber 110 picks up the microseismic signal propagating to the monitoring well 20 through the distributed acoustic sensing (DAS) located in the monitoring well 20, and perceives the phase change of the Rayleigh backscattering light caused by the microseismic signal by using the phase-sensitive optical time domain reflectometry (Φ-OTDR).

[0056] In the present embodiment, the downhole signal collection unit 130 is used to collect the microseismic signal of the monitoring well 20 picked up by the downhole optical fiber 110, and separate, amplify and transmit the optical signal of the downhole optical fiber 110.

[0057] Specifically, in the present embodiment, the optical signal collection unit located in the monitoring well 20, including but not limited to optical circulators and optical amplifiers, separates the input light and reflected light of the downhole optical fiber 110, amplifies the amplitude of the optical signal, and transmits it.

[0058] In the present embodiment, the submarine optical fiber 120 is used to pick up the microseismic signal propagating to the seabed surface. The submarine optical fiber 120 picks up the microseismic signal propagating to the seabed surface through the distributed acoustic sensing (DAS) located on the seabed, and perceives the phase change of the Rayleigh backscattering light caused by the microseismic signal by using the phase-sensitive optical time domain reflectometry (Φ-OTDR).

[0059] In the present embodiment, the submarine signal collection unit 140 is used to collect the microseismic signal of the seabed surface picked up by the submarine optical fiber 120, and separate, amplify and transmit the optical signal of the submarine optical fiber 120.

[0060] Specifically, the submarine signal collection unit 140 includes but is not limited to optical circulators and optical amplifiers, and uses optical circulators and optical amplifiers to separate and amplify the optical signal of the submarine optical fiber 120.

[0061] In the embodiment, the control unit 150 is configured to supply power to the distribution unit 160, and to perform GPS positioning and time calibration on the downhole signal acquisition unit 130 and the seabed signal acquisition unit 140, to obtain microseismic acquisition positioning data and timing data, and to transmit the obtained microseismic acquisition positioning data and timing data to the wireless transmission unit 180.

[0062] Specifically, in the embodiment, the control unit 150 includes a power supply, a GPS positioning device, and a time calibration device, and is configured to perform GPS positioning and time calibration on the downhole and seabed signal acquisition units, to supply power to the distribution unit 160, and to transmit the obtained microseismic acquisition positioning and timing data to the wireless transmission unit 180.

[0063] In the embodiment, the distribution unit 160 is configured to distribute optical signals to the downhole optical fiber 110 and the seabed optical fiber 120, and to transmit the combined microseismic signals returned by the downhole optical fiber 110 and the seabed optical fiber 120 to the signal conversion unit 170.

[0064] Specifically, in the embodiment, the distribution unit 160 includes but is not limited to a broadband light source, an optical switch, a wavelength division multiplexer, a distributor, etc., and is configured to perform multi-channel modulation on the optical signals of the broadband light source and distribute them to the downhole optical fiber 110 and the seabed optical fiber 120, and to combine and transmit the optical signals returned by the downhole optical fiber 110 and the seabed optical fiber 120 to the signal conversion unit 170.

[0065] In the embodiment, the signal conversion unit 170 is configured to convert the combined microseismic signals into data signals and transmit them to the wireless transmission unit 180.

[0066] Specifically, in the embodiment, the signal conversion unit 170 includes but is not limited to a coherent receiver and a dynamic demodulator, etc., and is configured to receive the optical signals transmitted by the distribution unit 160, to perform wavelength division multiplexing on the multi-channel optical signals, to demodulate them into corresponding vibration signals respectively, to convert them into data signals, and to transmit the data signals to the wireless transmission unit 180.

[0067] In the embodiment, the wireless transmission unit 180 is configured to encode, compress, and modulate the received data signals, and to transmit the data signals wirelessly to the wireless receiving unit 190 located in the monitoring center.

[0068] Specifically, in the embodiment, the wireless transmission unit 180 includes but is not limited to a controller, an encoder, a radio frequency front end, an antenna, etc., and is configured to encode, compress, and modulate the data signals transmitted by the control unit 150 and the signal conversion unit 170, and to transmit the data signals in the form of wireless signals to the cloud through a 5G cellular network.

[0069] In the embodiment, the wireless receiving unit 190 transmits the received data signal to the data analysis unit 1110 after filtering, amplifying and decoding.

[0070] Specifically, in the embodiment, the wireless receiving unit 190 includes but is not limited to an antenna, a filter, an amplifier, a decoder, etc., and transmits the 5G wireless signal received from the cloud after filtering, amplifying and decoding to the data analysis unit 1110.

[0071] In the embodiment, the data analysis unit 1110 analyzes and processes the data signal to monitor and identify the state of the fault 50 in real time.

[0072] Specifically, in the embodiment, the data analysis unit 1110 includes a high-performance computing workstation and a data analysis program therein to analyze and process the data transmitted by the wireless receiving unit 190.

[0073] In the embodiment, the transmission process of the microseismic signal in the system is as follows: downhole / subsea optical fiber 120→downhole signal acquisition unit 130 / subsea signal acquisition unit 140→distribution unit 160→signal conversion unit 170→wireless transmitting unit 180→wireless receiving unit 190→data analysis unit 1110.

[0074] The subsea CO2 storage-induced fault activation microseismic monitoring system 100 of the embodiment comprehensively adopts downhole monitoring and subsea monitoring means, improves the redundancy of the monitoring system, and makes the positioning of the seismic source more accurate.

[0075] The embodiment also provides a method for identifying subsea CO2 storage-induced fault activation, and a monitoring area is arranged with the subsea CO2 storage-induced fault activation microseismic monitoring system 100.

[0076] Figure 2 A flowchart of the method for identifying subsea CO2 storage-induced fault activation in the embodiment is shown. Specifically, as shown in Figure 2 the method for identifying subsea CO2 storage-induced fault activation provided by the embodiment includes the following steps S100 to S500.

[0077] In one implementation of the embodiment, an analytical solution model of reservoir fluid pressure in CO2 geological storage is used to estimate the influence range of subsea CO2 geological storage microseismic monitoring, and the monitoring area is determined based on the influence range.

[0078] Exemplarily, the embodiment uses an analytical solution model of reservoir fluid pressure in CO2 geological storage to estimate the range of subsea CO2 geological storage microseismic monitoring.

[0079] Assuming that the reservoir 60 is a saturated aquifer, homogeneous and isotropic, with constant thickness H, and that after CO2 injection a steady-state isothermal two-phase flow is formed with salt water, the CO2 plume is radially symmetric with the injection well 10 as the center. As shown in Figure 3 the radius of the CO2 enrichment zone, the CO2 plume front transition zone 40, and the CO2 pressure influence zone can be estimated according to the following formula.

[0080]

[0081] wherein r1 is the radius of the CO2 enrichment zone, r2 is the radius of the CO2 plume front transition zone 40, and r3 is the radius of the CO2 pressure influence zone, k w = k c = 0.5; μ w and μ c are the viscosities of the salt water and CO2 in the reservoir 60, respectively, which are estimated according to the temperature and pressure of the reservoir 60 based on the logging data; V c is the total volume of the injected CO2; φ is the porosity of the reservoir 60; S is the storage coefficient of the reservoir 60; T is the transmissivity of the reservoir 60; t is the total time of CO2 injection; and u0 is a dimensionless time, usually taken as 0.4-0.6.

[0082] This embodiment estimates the monitoring range in advance according to an actual seabed CO2 geological storage project, so that the arrangement of the monitoring facilities is more reasonable and targeted.

[0083] Specifically, according to the position of the injection well 10 and the geology and logging data of the CO2 geological storage site in the sea area, the influence range of the injected CO2 during the monitoring period of the CO2 geological storage is estimated through multi-field and multi-phase numerical simulation or analytical solution of CO2 injection, including the CO2 enrichment zone, the CO2 plume front transition zone 40, and the CO2 pressure influence zone, and then the monitoring range is preliminarily determined according to the range.

[0084] Figure 3 FIG. 1 shows a schematic diagram of the monitoring range estimation and monitoring facility arrangement in the identification method of seabed CO2 storage-induced fault activation according to an embodiment of the present application. As shown in Figure 3As shown, in the present embodiment, the influence range includes the CO2 enrichment zone, the CO2 plume front transition zone 40, and the CO2 pressure influence zone; the monitoring well 20 is arranged in the annular range of the CO2 plume front transition zone 40, and a distributed downhole optical fiber 110 is arranged in the monitoring well 20 to a certain depth of the reservoir 60 upper portion; the injection well 10 is arranged in the center of the CO2 enrichment zone, and a plurality of distributed seabed optical fibers 120 are arranged in a uniform radial manner on the seabed surface centering on the injection well 10; the control unit 150, the distribution unit 160, the signal conversion unit 170, and the wireless transmission unit 180 are arranged on the offshore platform 30 of the injection well 10, and the wireless receiving unit 190 and the data analysis unit 1110 are arranged in the offshore or onshore monitoring center.

[0085] Specifically, the area where the fault 50 possibly exists in the monitoring range is evaluated by interpreting the geological and logging data of the CO2 geological storage site in the sea area, such as Figure 4 As shown, the permanent monitoring well 20 is arranged on the offshore platform 30 near the area where the fault 50 possibly exists on the side of the estimated annular range of the CO2 plume front transition zone 40, and a distributed acoustic optical fiber (DAS) is arranged in the monitoring well 20 to a certain depth of the reservoir 60 upper portion, and eight distributed acoustic optical fibers (DAS) are arranged in a uniform radial manner on the seabed surface centering on the injection well 10, with the distal ends of the eight distributed acoustic optical fibers (DAS) being about (r2+r3) / 2 away from the injection well 10; the control unit 150, the distribution unit 160, the signal conversion unit 170, and the wireless transmission unit 180 are arranged on the offshore platform 30 of the injection well 10, and the wireless receiving unit 190 and the data analysis unit 1110 are arranged in the offshore or onshore monitoring center.

[0086] After the monitoring facility is arranged, the microseismic monitoring system 100 induced by the seabed CO2 storage and fault activation is initialized: the power supply is turned on and power is supplied to the distribution unit 160, the downhole signal acquisition unit 130 and the seabed signal acquisition unit 140 are positioned by GPS, and the time is calibrated.

[0087] Specifically, the monitoring system is initialized by the control unit 150, the power supply of the control unit 150 is turned on and power is supplied to the distribution unit 160, the downhole signal acquisition unit 130 and the seabed signal acquisition unit 140 are instructed by the distribution unit 160 to obtain the position, length and direction of the downhole optical fiber 110 and the seabed optical fiber 120, and return to the GPS positioning device in the control unit 150, so as to calculate the spatial position of each measuring point on the downhole optical fiber 110 and the seabed optical fiber 120, and the signal acquisition start time of the downhole signal acquisition unit 130 and the seabed signal acquisition unit 140 is calibrated by the time calibration device in the control unit 150, and the positioning data and time data are transmitted to the data analysis unit 1110 and stored for use by the communication of the wireless transmission unit 180 and the wireless receiving unit 190.

[0088] Step S100, acquiring the data signal in the seabed CO2 injection process.

[0089] When a microseismic event occurs in the formation, seismic waves (including P waves and S waves) are transmitted to the downhole optical fiber 110 and the seabed optical fiber 120 location, and cause the phase change of Rayleigh backscattered light, the optical signal is transmitted to the signal conversion unit 170 through the acquisition unit and the distribution unit 160, and after separation and demodulation, it is converted into a data signal, and then transmitted to the data analysis unit 1110 through the communication of the wireless transmission unit 180 and the wireless receiving unit 190. In this embodiment, the microseismic signal in the CO2 injection process is collected by the monitoring system, and after pre-processing of the data including noise suppression and data cleaning, the data signal in the CO2 injection process is obtained.

[0090] Exemplarily, the empirical mode decomposition method (EMD) is used to suppress the noise of the collected microseismic signal, and the accuracy of the microseismic signal is verified and cleaned through the correlation of the waveforms between different monitoring positions.

[0091] The empirical mode decomposition method (EMD) is used to suppress the noise of the collected microseismic signal, and the accuracy of the microseismic signal is verified and cleaned through the correlation of the waveforms between different monitoring positions.

[0092] First, the microseismic signal is decomposed into a series of intrinsic mode functions (IMF), and the intrinsic mode functions obtained by decomposition are arranged from high frequency to low frequency, and then a band-pass filter is constructed according to the empirical mode decomposition result. The intrinsic mode functions obtained by decomposition are screened, and then the filtered microseismic signal is reconstructed through the screened intrinsic mode functions.

[0093] In one implementation of the embodiment, in the process of acquiring the data signal in the seabed CO2 injection process, it also includes judging and eliminating abnormal microseismic signals; wherein the Pearson correlation coefficient between the waveforms between different monitoring positions is used to judge the abnormal microseismic signals.

[0094] Exemplarily, the accuracy of the microseismic signal is verified through the correlation of the waveforms between different monitoring positions, and the Pearson correlation coefficient between the waveform w A (t) of position A and the waveform w B (t) of position B is:

[0095]

[0096] Wherein, and are the waveforms w A (t) and w BThe mean value of (t). After obtaining the Pearson correlation coefficient between the microseismic signals of all monitoring positions of the same optical fiber, the microseismic signals with a correlation coefficient less than 0.7 between other monitoring positions are considered to be abnormal, and are cleaned.

[0097] Step S200, calculating the distance between the monitoring position and the seismic source based on the data signal to locate the position of the seismic source.

[0098] Figure 5 The flow chart for determining the position of the seismic source in the method for identifying the activation of the fault induced by the seabed CO2 storage according to an embodiment of the application is shown. As shown in the figure, in an implementation manner of the embodiment, the step of calculating the distance between the monitoring position and the seismic source based on the data signal comprises steps S210 to S230. Figure 5

[0099] Step S210, performing first arrival picking of the waveform of each monitoring position by using the long-short time window energy ratio method;

[0100] Step S220, obtaining the time difference between P wave and S wave and the wave velocity of P wave and S wave according to the waveform of the monitoring position;

[0101] Step S230, calculating the distance between the monitoring position and the seismic source according to the time difference between P wave and S wave and the wave velocity of P wave and S wave.

[0102] In the embodiment, the long-short time window energy ratio method is used to perform first arrival picking of the waveform of each monitoring position, wherein the calculation formula of the long-short time window energy ratio is as follows:

[0103]

[0104] Wherein, w i is the value of the i th sampling point; N0 is the sampling index of the current time point; N S is the length of the short time window (sampling points); N L is the length of the long time window (sampling points). When the long-short time window energy ratio STA / LTA exceeds a certain threshold value, it is determined that a microseismic event occurs, and the arrival time is picked up. In particular, the threshold value is 1.5.

[0105] Preferably, the embodiment uses the hodograph method to calculate the estimated distance between the monitoring position and the seismic source according to the time difference between P wave and S wave and the wave velocity of P wave and S wave The formula is as follows:

[0106]

[0107] Wherein, Δt is the time difference between P wave and S wave; c p and c s ​Wave velocity of P and S waves respectively.

[0108] In an implementation form of the embodiment, ray tracing is used in combination with an arithmetic optimization algorithm to obtain the optimal source location.

[0109] Specifically, the root mean square average of the distance errors between all monitoring positions and the source is used as the optimization target parameter, that is:

[0110]

[0111] where N is the number of effective monitoring positions; is the estimated distance between the i-th monitoring position and the source; d i is the actual distance between the i-th monitoring position and the current specified source location. Ray tracing is used in combination with an optimization algorithm to obtain the optimal source location. In particular, the arithmetic optimization algorithm (AOA) is used. The spatial distribution of the source of all microseismic events is plotted as shown in Figure 4 .

[0112] In step S300, the source moment tensor and the moment magnitude are obtained based on the source location, and the source mechanism solution is obtained based on the source moment tensor.

[0113] In an implementation form of the embodiment, obtaining the source moment tensor based on the source location, and obtaining the moment magnitude and the source mechanism solution based on the source moment tensor include:

[0114] Based on the source location, the amplitudes of P and S waves at the monitoring positions are obtained; a vector w composed of the amplitudes of P and S waves at the monitoring positions is obtained, and an inversion vector of the source moment tensor M is obtained based on the vector w composed of the amplitudes. G is an over-determined matrix; based on the inversion vector The normalized source mechanism solution is determined.

[0115] The embodiment uses the moment tensor inversion based on amplitude information to invert the source mechanism. Specifically, according to the Green function formula of a point source in an elastic medium, the amplitudes of P and S waves at a certain monitoring position are respectively:

[0116]

[0117] where the subscripts i, j, and k represent three coordinate directions in three-dimensional space; d is the distance between the source and the monitoring position; p is the density; n i , n j , n k are three components of the unit direction vector of the monitoring position relative to the source; d ij is the Kronecker symbol; Mjk The moment tensor of the seismic source. The P-wave and S-wave amplitudes at all monitoring positions form a vector:

[0118] The vector reconstructed with the moment tensor M of the seismic source The relationship therebetween is thus constructed:

[0119]

[0120] Wherein, G is an over-determined matrix. The inversion is obtained by the following formula:

[0121]

[0122] Wherein, in the embodiment, the moment tensor M of the seismic source is represented by the seismic moment M0 and the normalized focal mechanism solution , so as to obtain the focal mechanism solution

[0123]

[0124] The moment magnitude M is obtained according to the seismic moment M0 (unit: N·m): w

[0125]

[0126] In an implementation manner of the embodiment, further comprising: performing eigenvalue decomposition on the normalized focal mechanism solution to obtain an isotropic source tensor, a compensated linear vectorial source tensor and a double couple source tensor; and drawing a focal mechanism beach ball of all microseismic events based on the isotropic source tensor, the compensated linear vectorial source tensor and the double couple source tensor.

[0127] According to the source position, the moment tensor inversion based on the amplitude information is carried out, the corresponding moment magnitude and the normalized focal mechanism solution are obtained, and the focal mechanism beach ball of the microseismic event is drawn.

[0128] Specifically, the normalized focal mechanism solution is subjected to eigenvalue decomposition to obtain an isotropic source tensor , a compensated linear vectorial source tensor and a double couple source tensor

[0129]

[0130] Then, the focal mechanism beach ball of all microseismic events is drawn, as shown in Figure 4 .

[0131] ​Step S400, taking the focal mechanism solution as a clustering parameter, performing spatial clustering analysis on all microseismic events in the seabed CO2 injection process to obtain a potential blind fault corresponding to each cluster.

[0132] That is, performing density-based spatial clustering analysis on all microseismic events in the CO2 injection process, dividing into several clusters, and each cluster corresponding to a potential blind fault.

[0133] In an implementation manner of the embodiment, the minimum number k of microseismic events in a cluster is: Wherein, m is the number of microseismic events.

[0134] Figure 6 An example diagram of the recognition method of the seabed CO2 storage induced fault activation in the embodiment of the application is shown, which shows the focal mechanism inversion, the focal mechanism solution and the spatial clustering analysis of the microseismic events. Figure 6 As shown in the embodiment, the normalized focal mechanism solution is taken as a clustering parameter to perform density-based spatial clustering analysis (DBSCAN) on all microseismic events in the CO2 injection process. Assuming that there are m microseismic events, the minimum number of microseismic events in a cluster is:

[0135] k = int (m / 25)

[0136] The neighborhood radius r of the clustering object a is:

[0137]

[0138] Wherein, Γ(*) is the gamma function; is the distance between the normalized focal mechanism solutions of microseismic events i and j; The maximum distance between the normalized focal mechanism solutions of all m microseismic events is represented as D. For a microseismic event i, the microseismic event j satisfying is considered to fall within the neighborhood of the microseismic event i. All m microseismic events are traversed, and when there are at least k microseismic events in the neighborhood of a microseismic event, it is considered to satisfy the dense condition, and all other microseismic events in the neighborhood constitute a set Ω. Then all microseismic events that also satisfy the dense condition are found in the set Ω, and are incorporated into Ω, and the cycle is repeated until no microseismic event that satisfies the dense condition can be added, and then all microseismic events in the set Ω constitute a cluster. Finally, all m microseismic events are divided into several clusters by this method, and each cluster corresponds to a potential blind fault, as shown in Figure 4 .

[0139] This embodiment demonstrates the ability to identify potential hidden faults by performing cluster analysis on all microseismic events during the CO2 injection process.

[0140] Step S500: For all microseismic events on each potential hidden fault, perform a linear fitting of magnitude-frequency based on the moment magnitude to obtain the seismic b-value of seismic activity on the fault plane, and identify fault activation based on the seismic b-value.

[0141] In this embodiment, a logarithmic linear fit is performed on the GR relationship of earthquake magnitude-frequency on the fault plane to obtain the b value, and the fault activation is identified based on the b value.

[0142] This embodiment identifies fault activation based on the b-value of seismic activity on the fault plane, enabling early prediction of fault tectonic activity before the occurrence of earthquakes of larger magnitudes.

[0143] Specifically, in one implementation of this embodiment, when the earthquake b value is ≤1, the fault 50 is determined to have entered the activation stage.

[0144] Figure 7 This diagram shows the magnitude-frequency (GR) relationship fitting and corresponding b-value plot of seismic activity on a fault in an identification method for fault activation induced by seabed CO2 sequestration, as described in an embodiment of this application. Figure 7 As shown, fault activation is identified based on the b-value of seismic activity on the fault plane. For all microseismic events in each cluster, or rather, on each potential fault, statistical analysis is performed according to moment magnitude, and a log-linear fit is applied to the magnitude-frequency (GR) relationship as follows:

[0145] log 10 N = a - bM w

[0146] Where N is the moment magnitude greater than M w The number of microseismic events, such as Figure 7 As shown. Finally, the activation of fault 50 is identified based on the fitted b value. When b≤1, fault 50 is determined to have entered the activation stage.

[0147] In summary, the application comprehensively adopts downhole monitoring and seabed monitoring means, improves the redundancy of the monitoring system, makes the positioning of the seismic source more accurate, can realize real-time monitoring of the fault state in seabed CO2 geological storage, and identify possible fault activation; the application estimates the monitoring range in advance according to the actual seabed CO2 geological storage project, so that the arrangement of the monitoring facility is more reasonable and targeted; the application carries out clustering analysis on all microseismic events in the CO2 injection process, and has the ability to identify potential blind faults; the application identifies fault activation according to the b value of seismic activity on the fault plane, and can predict the tectonic activity of the fault in advance before a large magnitude earthquake occurs. Therefore, the application effectively overcomes the various shortcomings in the prior art and has a high industrial utilization value.

[0148] The above embodiments only exemplarily illustrate the principles and effects of the application, and are not used to limit the application. Any person skilled in the art can modify or change the above embodiments without departing from the spirit and scope of the application. Therefore, all equivalent modifications or changes completed by those skilled in the art without departing from the spirit and technical idea disclosed by the application should be covered by the claims of the application.

Claims

1. A subsea CO2 sequestration induced fault activation microseismic monitoring system, characterized in that, The system comprises: a downhole optical fiber and a downhole signal acquisition unit located in a monitoring well, a seabed optical fiber and a seabed signal acquisition unit located on the seabed of a seabed centering on an injection well, a control unit, a distribution unit, a signal conversion unit and a wireless transmitting unit located on a platform of the injection well, a wireless receiving unit and a data analysis unit located in a monitoring center; the downhole optical fiber is used to pick up microseismic signals propagating to the monitoring well; the downhole signal acquisition unit is used to acquire the microseismic signals of the monitoring well picked up by the downhole optical fiber; the seabed optical fiber is used to pick up microseismic signals propagating to the seabed surface; the seabed signal acquisition unit is used to acquire the microseismic signals of the seabed surface picked up by the seabed optical fiber; the control unit is used to power the distribution unit, GPS position and time calibration of the downhole signal acquisition unit and the seabed signal acquisition unit, acquisition of microseismic acquisition positioning data and timing data, and transmission of the acquired microseismic acquisition positioning data and timing data to the wireless transmitting unit; the distribution unit is used to distribute optical signals to the downhole optical fiber and the seabed optical fiber, and to transmit the combined microseismic signals returned by the downhole optical fiber and the seabed optical fiber to the signal conversion unit; the signal conversion unit converts the combined microseismic signals into data signals and sends them to the wireless transmitting unit; the wireless transmitting unit wirelessly transmits the received data signals to the wireless receiving unit located in the monitoring center; the wireless receiving unit transmits the received data signals to the data analysis unit; the data analysis unit analyzes the data signals and monitors the state of the fault in real time and identifies the activation.

2. A method of identifying seabed CO2 storage-induced fault reactivation, characterized by, The method comprises: acquiring data signals during seabed CO2 injection; calculating the distance between the monitoring position and the seismic source based on the data signals to locate the seismic source position; obtaining the seismic source moment tensor and moment magnitude based on the seismic source position, and obtaining the seismic source mechanism solution based on the seismic source moment tensor; taking the seismic source mechanism solution as a clustering parameter to perform spatial clustering analysis on all microseismic events during seabed CO2 injection, and obtaining a potential blind fault corresponding to each cluster; performing a linear fitting of magnitude-frequency on all microseismic events on each potential blind fault based on the moment magnitude to obtain the seismic b value of seismic activity on the fault plane, and identifying the fault activation based on the seismic b value.

3. The method of claim 2, wherein the method is characterized by, An analytical solution model of reservoir fluid pressure in CO2 geological storage is used to estimate the influence range of seabed CO2 geological storage microseismic monitoring, and the monitoring area is determined based on the influence range. The influence range includes a CO2 enrichment area, a CO2 plume front transition area, and a CO2 pressure influence area; a monitoring well is arranged in the CO2 plume front transition area, and a distributed downhole optical fiber is arranged in the monitoring well to a certain depth of the upper reservoir; an injection well is arranged in the center of the CO2 enrichment area, and a plurality of distributed submarine optical fibers are arranged on the seabed surface in a uniform radial manner around the injection well; a control unit, a distribution unit, a signal conversion unit, and a wireless transmission unit are arranged on the offshore platform of the injection well, and a wireless receiving unit and a data analysis unit are arranged in a near-shore or on-shore monitoring center.

4. The method of claim 2, wherein, In the data signal obtained in the process of injecting CO2 into the seabed, an abnormal microseismic signal is judged and removed; wherein the abnormal microseismic signal is judged by the Pearson correlation coefficient between waveforms between different monitoring positions.

5. The method of claim 4, wherein, The distance between the monitoring position and the seismic source is calculated based on the data signal, comprising: The first arrival of the waveform of each monitoring position is picked up by using a long-short time window energy ratio method; The arrival time difference between P wave and S wave and the wave velocity of P wave and S wave are obtained according to the waveform of the monitoring position; The distance between the monitoring position and the seismic source is calculated according to the arrival time difference between P wave and S wave and the wave velocity of P wave and S wave.

6. The method of claim 5, wherein, The optimal seismic source position is obtained by ray tracing combined with an arithmetic optimization algorithm.

7. The method of claim 2, wherein the method is characterized by, The seismic moment tensor is obtained based on the seismic source position, and the moment magnitude and the focal mechanism solution are obtained based on the seismic moment tensor, comprising: The amplitudes of P wave and S wave of the monitoring position are obtained based on the seismic source position; An amplitude vector w of P and S waves at monitoring positions P is obtained, and a focal moment tensor M inversion vector is obtained based on the amplitude vector w G is an over-determined matrix; based on the inversion vectors determining a normalized focal mechanism solution.

8. The method of claim 7, wherein, Further comprising: The normalized focal mechanism solution is decomposed to obtain an isotropic source tensor, a compensated linear vector source tensor, and a double couple source tensor; The focal mechanism beach balls of all microseismic events are drawn based on the isotropic source tensor, the compensated linear vector source tensor, and the double couple source tensor.

9. The method of claim 2, wherein the method is characterized by, The minimum number k of microseismic events in a cluster is: k = int(m / 25) Wherein, m is the number of microseismic events.

10. The method of claim 2, wherein, When the seismic b value is less than or equal to 1, it is determined that the fault enters the activation stage.

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