Читать книгу Geophysical Monitoring for Geologic Carbon Storage - Группа авторов - Страница 16

Seismic monitoring can use active seismic surveys and/or microseismic events induced by CO₂ injection and migration. Microseismic monitoring uses sensors/geophones deployed on the surface covering the monitoring region, and/or sensors/geophones in one or more boreholes to monitor induced microseismic events smaller than what surface seismic arrays can detect. For cost‐effective microseismic monitoring, we need to understand how many sensors/geophones are needed, and how to distribute them spatially to monitor targets of interest, such as the CO₂ storage reservoir, caprock, faults, and so on. In Chapter 4, Chen and Huang present a methodology to determine the optimal number of geophones using a surface seismic monitoring network or a borehole geophone array for cost‐effective monitoring of target regions. They determine the optimal number of seismic stations based on the trade‐off curve of the event location accuracy versus the total number of seismic stations. They design an optimal microseismic monitoring network based on widely accepted guiding principles, and the relationship between the location accuracy of microseismic events and the total number of seismic stations. The method is based on the trade‐off curve between the mean location accuracy and the number of seismic stations. In practical applications, three‐component geophones can provide more useful information of shear‐wave signals to improve microseismic monitoring compared with one‐component geophones.

Active seismic monitoring uses time‐lapse seismic reflection/transmission data. The underlining physical principle of this monitoring technique is based on the effects of (supercritical) carbon dioxide on subsurface elastic parameters. CO₂ injection and migration alter elastic parameters such as compressional and shear velocities, density, and seismic attenuations in isotropic geologic formations, and also anisotropic parameters in anisotropic geologic formations. Studies of rock physics on the effects of CO₂ injection and migration form the foundation of time‐lapse seismic monitoring for geologic carbon storage. In Chapter 5, Nakagawa and Kneafsey present laboratory measurements of the seismic response of fractured sandstone during geologic carbon sequestration. They employ a modified resonant bar technique to make laboratory measurements, and give the dynamic Young's modulus, shear modulus, and attenuation in core samples with supercritical CO₂ injected, within a sonic frequency band of ~1 kHz to ~2 kHz. They use X‐ray CT to understand the distribution of supercritical CO₂ injected into the core samples. Their laboratory experiment results show that changes in seismic‐wave velocities and attenuations strongly depend on the fracture orientation. In Chapter 6, Delaney et al. use laboratory ultrasonic experiments to study rock physics properties of rhyolite and carbonate samples, and the effects of pressure, temperature, porosity, and fluid saturation on their rock properties. In their experiments, they vary the pore‐filling fluids, effective pressures, and temperatures. They find that the framework composition, porosity, heterogeneities, temperature, effective pressure and pore‐filling fluids are first‐order controls on trends in elastic parameters and wave attenuation. Their findings could provide insight on using amplitude versus offset (AVO) for seismic monitoring. Their results show that the quality factor of compressional waves measuring compressional‐wave attenuation is inversely proportional to rock porosity and is weakly dependent on temperature. These results reveal the relationships of the ultrasonic velocity and the quality factor as a function of both temperature and effective pressure.

Time‐lapse 3D seismic monitoring, or 4D seismic monitoring, is considered as the most effective tool for 3D subsurface monitoring of CO₂ injection and migration. However, time‐lapse 3D seismic surveys and data processing are costly and time consuming. For the similar purpose of optimal design of a microseismic monitoring network, Gao et al. in Chapter 7 introduce a numerical method for designing optimal time‐lapse seismic monitoring surveys by analyzing sensitivities of elastic waves in isotropic and anisotropic media with respect to reservoir geophysical property changes. Conventional seismic surveys are designed based on seismic‐wave illumination of the entire subsurface imaging region, and require a large number of sources and receivers to produce high‐resolution images of the subsurface. By contrast, time‐lapse seismic monitoring is not designed to image the entire subsurface region, but only the target monitoring regions, such as the CO₂ storage reservoir, caprock, and faults. Therefore, time‐lapse seismic monitoring needs only seismic information from such regions, rather than from the entire subsurface region. The optimal design of time‐lapse seismic surveys is based on elastic‐wave sensitivity analysis, that is, numerical modeling of elastic‐wave changes with respect to changes of geophysical properties within target monitoring regions. The method numerically solves the elastic‐wave sensitivity equations obtained by differentiating the elastic‐wave equations with respect to geophysical parameters, such as density, compressional‐ and shear‐wave velocities, and saturation parameters, in isotropic and anisotropic media. Receivers should be placed in surface regions for surface seismic surveys or borehole locations for vertical seismic profiling (VSP) surveys with significant values of elastic‐wave sensitivity energies. The number of receivers needed for cost‐effective time‐lapse seismic monitoring is only a fraction of a regular 3D seismic survey.

The 3D surface seismic monitoring has the advantage of monitoring a large subsurface area to track CO₂ migration in the 3D space. However, seismic imaging/monitoring resolution decreases with the depth, particularly for CO₂ storage at geologic formations at several kilometers in depth. Compared with surface seismic monitoring, VSP monitoring improves seismic imaging/monitoring resolution in the deep region when receivers are placed in the deep region of the subsurface. The image resolution of VSP monitoring is usually twice that of surface seismic monitoring. The limitation of VSP monitoring is that the lateral monitoring range is smaller than surface seismic monitoring.

VSP surveys use active seismic sources at various offset locations (offset VSP), or along various walkway lines from the monitoring well (walkaway VSP), or using a 2D surface source distribution (3D VSP). Offset VSP monitoring uses only a few offset source points, and has the lowest cost among the three different types of time‐lapse VSP survey. However, offset VSP can monitor only in the sparse azimuthal directions along a monitoring well to offset source directions. 3D VSP monitoring is the most expensive among the three VSP monitoring approaches, with the highest spatial coverage of the monitoring region. The walkaway VSP monitoring is the trade‐off between the offset VSP monitoring and 3D VSP monitoring.

In Chapter 8, on offset VSP monitoring, Zhang and Huang study the capability of offset VSP imaging for monitoring CO₂ injection/migration, and present monitoring results at the Aneth CO₂‐EOR (Enhanced Oil Recovery) field in Utah. The offset VSP monitoring uses a permanent geophone string with 60 levels and 96 channels cemented into a monitoring well. Because of uncertainties in the offset VSP source locations during repeat VSP surveys, they present a method to use travel times of the downgoing VSP waves and double‐difference tomography to invert for the “true” VSP source locations. This approach addresses the source repeatability issue in practical offset VSP monitoring. Zhang and Huang apply wave‐equation migration imaging of the preprocessed and balanced time‐lapse offset VSP data from the Aneth CO₂‐EOR field and the inverted “true” VSP source locations to infer the reservoir changes. To reduce the imaging noise of the offset VSP data, they employ an angle‐domain imaging condition with reflection angle constraint for different offset VSP data sets to produce time‐lapse migration images, showing reservoir changes caused by CO₂ injection/migration along different offset directions are different, indicating an anisotropic CO₂ migration pattern relative to the injection wells.

In Chapter 9 on walkaway VSP monitoring, Wang et al. apply reverse‐time migration (RTM) to time‐lapse walkaway VSP data acquired at the SACROC CO₂‐EOR field in Scurry County, Texas, USA, to reveal changes in the reservoir caused by CO₂ injection and migration. Before they apply RTM to the data, they perform statics correction and amplitude balancing to the time‐lapse walkaway VSP data sets. To mitigate the image artifacts caused by the limited subsurface seismic illumination of the walkaway VSP surveys, they analyze and process the RTM images in the angle domain to greatly improve the image quality.

Because of limited seismic illumination of VSP surveys, migration imaging of VSP data often contains significant image artifacts, which can be alleviated using an angle‐domain imaging condition. This alleviation is tedious if not impossible for 3D VSP data. 3D least‐squares reverse‐time migration (LSRTM) is an alternative approach to addressing such a problem. To demonstrate the improved imaging capability of 3D LSRTM of 3D VSP data, Tan et al., in Chapter 10, apply the method to a portion of the 3D VSP data acquired at the Cranfield CO₂‐EOR field in Mississippi, USA, for monitoring CO₂ injection to obtain a high‐resolution 3D subsurface image. LSRTM solves for a reflectivity model by minimizing the difference between the observed data and modeled data. The advantages of LSRTM over RTM of VSP data include: (1) LSRTM significantly improves the spatial resolution of the layer images, and (2) LSRTM extends the horizontal imaging region to areas that cannot be imaged using RTM.

Besides time‐lapse seismic imaging, quantifying changes of subsurface geophysical properties caused by CO₂ injection/migration can provide crucial information of CO₂ plumes. In Chapter 11, Lin et al. present a double‐difference seismic‐waveform inversion method to jointly invert time‐lapse seismic data for reservoir changes of elastic parameters. Inverting individual time‐lapse seismic data sets separately may result in significant inversion artifacts and inaccurate inversion results. Double‐difference acoustic‐ or elastic‐waveform inversion constrains time‐lapse seismic data sets with each other to improve the robustness of inversion of time‐lapse changes and reduce inversion artifacts. In Lin et al.'s double‐difference seismic‐waveform inversion methods, they employ an energy‐weighted preconditioner, a spatial priori information (target monitoring regions), and a modified total‐variation regularization scheme to improve the inversion accuracy of changes of subsurface geophysical properties. They validate the method using time‐lapse walkaway VSP data acquired at the SACROC CO₂‐EOR field, and reveal the velocity decrease in the geologic formation where CO₂ was injected.

Multicomponent seismic surveys acquire not only compressional‐wave signals, but also shear‐wave signals that carry useful information for high‐resolution subsurface site characterization and monitoring. When using shear‐wave sources, the multicomponent seismic surveys record the full nine‐component elastic wavefields, which are the most complete seismic data. Such data contain compression‐to‐compression and shear‐to‐shear waves in addition to converted waves including compression‐to‐shear and shear‐to‐compression waves. Multicomponent seismic data are far more sensitive to fracture zones than compressional‐wave data, allowing improved characterization/monitoring of potential leakage pathways or preferential flow directions compared with one‐component data. In Chapter 12, on site characterization using multicomponent seismic data, DeVault et al. describe joint inversion of multicomponent seismic data for deriving elastic parameters from multicomponent data and demonstrate the unique advantages for geophysical CO₂ reservoir characterization. They present results of joint inversion for characterizing the Duperow CO₂‐bearing zone at Kevin Dome, Montana, USA. They demonstrate that the additional amplitude and polarization information contained in multicomponent data allows for the estimation of shear impedance, density, and azimuthal anisotropic parameters with much greater accuracy than using compressional‐wave seismic data.

In Chapter 13, Mur et al. develop forward modeling workflows for predicting fluid and pressure effects resulting from supercritical CO₂ (scCO₂) injection in a sandstone reservoir using 4D reflection seismic data and well logs. They use a 3D prestack seismic data set, two 3D seismic poststack volumes, and a wireline log from the sandstone reservoir, to perform forward modeling and predict reservoir seismic response of fluid substituted CO₂ as a component of the pore‐filling fluid mix in a reservoir unit. They use time‐lapse 3D seismic data acquired before and after CO₂ injection and postinjection common midpoint stacks to determine regions of possible fluid density and pore pressures signatures. The lateral changes in amplitude versus offset (AVO) can be an indicator of pore‐filling fluid changes. They implement the Aki‐Richards method to model reflected wave amplitudes at increasing offset angles on time‐lapse prestack seismic data from the Cranfield Field, Mississippi, USA. They present results on the effects of seismic‐wave reflectivity caused by the injection of CO₂ in a sandstone reservoir at Cranfield, and predict the fluid effects of CO₂ presence in the reservoir by applying fluid substitutions to produce reservoir property models and compare these effects with an actual 4D seismic survey.