In some reservoir applications, seismic data are acquired with downhole sources and receivers. If the receiver is stationed at various depth levels in a well and the source remains on the surface, the measurement is called vertical seismic profiling (VSP). This technique produces a high-resolution, 2D image that begins at the receiver well and extends a short distance (a few tens of meters or a few hundred meters, depending on the source offset distance) toward the source station. This image, a 2D profile restricted to the vertical plane passing through the source and receiver coordinates, is useful in tying seismic responses to subsurface geologic and engineering control. If the source is deployed at various depth levels in one well and the receiver is placed at several depth stations in a second well, the measurement is called crosswell seismic profiling (CSP). Images made from CSP data have the best spatial resolution of any seismic measurement used in reservoir characterization because a wide range of frequencies is recorded.
Collecting seismic data requires an energy source to generate waves and sensors to receive those waves. The appropriate energy source and receiver depend on the location and the application. This article describes different types of equipment used for seismic data acquisition. A variety of seismic sources exist that can apply vertical impulse forces to the surface of the ground. These devices are viable energy sources for onshore seismic work.
A variety of seismic sources exist that can apply vertical impulse forces to the surface of the ground. These devices are viable energy sources for onshore seismic work. Included in this source category are gravity-driven weight droppers and other devices that use explosive gases or compressed air to drive a heavy pad vertically downward. Multiple references describe these types of sources. Chemical-explosive energy sources are popular for onshore seismic surveys but are prohibited at some sites because of environmental conditions, cultural restrictions, or federal and state regulations. Chemical explosives are no longer used as marine energy sources for environmental and ecological reasons. Field tests should always be made before an extensive seismic program is implemented. First, it should be determined whether the selected impulsive source creates adequate energy input to provide data with an appropriate signal-to-noise ratio and a satisfactory signal bandwidth at appropriate offset distances. Second, it is important to determine whether an impulsive source causes unwanted reverberations in shallow strata. Vibroseis energy sources are some of the more popular seismic source options for onshore hydrocarbon exploration.
The full elastic seismic wavefield that propagates through an isotropic Earth consists of a P-wave component and two shear (SV and SH) wave components. Marine air guns and vertical onshore sources produce reflected wavefields that are dominated by P and SV modes. Much of the SV energy in these wavefields is created by P-to-SV-mode conversions when the downgoing P wavefield arrives at stratal interfaces at nonnormal angles of incidence (Figure 1). Horizontal-dipole sources can create strong SH modes in onshore programs. No effective seismic horizontal-dipole sources exist for marine applications.
Binder, Gary (Colorado School of Mines) | Titov, Aleksei (Colorado School of Mines) | Tamayo, Diana (Colorado School of Mines) | Simmons, James (Colorado School of Mines) | Tura, Ali (Colorado School of Mines) | Byerley, Grant (Apache Corporation) | Monk, David (Apache Corporation)
In 2017, distributed acoustic sensing (DAS) technology was deployed in a horizontal well to conduct a time-lapse vertical seismic profiling (VSP) survey before and after each of 78 hydraulic fracturing stages. The goal of the survey was to more continuously monitor the evolution of stimulated rock throughout the treatment of the well. From two vibroseis source locations at the surface, time shifts of P-waves were observed along the well that decayed almost completely by the end of the treatment. A shadowing effect in the time shifts was observed that enables the height of the stimulated rock volume to be estimated. Using full wavefield modeling, the distribution of time shifts is well described by an equivalent medium model of vertical fractures that close as pressure declines due to fluid leak-off. Converted P to S waves were also observed to scatter off stimulated rock near some stages as confirmed with full wavefield modeling. The signal-to-noise ratio is a limitation of the current dataset, but recent improvements in DAS technology can enable stage-by-stage monitoring of the stimulated rock height, fracture compliance, and decay time as a well is completed.
Distributed Acoustic Sensing (DAS) has opened new possibilities for seismic monitoring of unconventional reservoirs. Using a laser interrogator to launch light pulses down a fiber optic cable, dynamic strain changes can be sampled along the cable from the phase shift of light backscattered to the interrogator (Hartog, 2017). Since the fiber optic cable can be permanently cemented outside the casing in a borehole, highly repeatable vertical seismic profiling (VSP) surveys can be acquired frequently without costly wireline geophone deployments that interfere with well treatment activities (Mateeva et al., 2017; Meek et al., 2017).
As described by Byerley et al., 2018, a unique interstage DAS VSP survey was conducted in 2017 during the stimulation of a horizontal well targeting the Wolfcamp formation in the Midland Basin, Texas. Using two vibroseis source locations offset about 1 mile from the heel and toe of the well, DAS data was acquired in the treatment well before and after each of 78 hydraulic fracturing stages. At the expense of fewer source locations, this type of acquisition allows the evolution of the stimulated rock volume (SRV) to be monitored on a stage-by-stage basis as the well is treated.
This paper presents an alternative solution for gas cloud imaging using full wavefield migration (FWM). The application of FWM method have been applied on both synthetic dataset with gas cloud event and existing field with gas cloud issue. The full wavefield migration is an inversion-based imaging algorithm that utilizes the complete reflection measurements: primaries as well as all multiples, both surface and internal to obtain the total reflections measurement. It combines the primary and higher order scattering reflection from the gas cloud to estimate the true amplitude response below the gas cloud. Successful applications to both synthetic and field data examples demonstrate that FWM improves the imaging illumination and resolution below gas cloud as compared to conventional migration.
Reverse time migration (RTM) involves zero-lag cross-correlation of forward extrapolated source function wavefields and backward extrapolated receiver wavefields. For a near surface with complex structures and velocity anomalies, forward propagating the source wavelet generates wavefields containing reflections, near-surface multiples, and scattered direct arrivals. The wavefields are recorded as upgoing arrivals contaminated by the same reflections, near-surface multiples, and scattered signals, which can be critical for imaging near-surface structures and scatterers.
Here, we develop a new depth migration, duplex reverse time migration (DRTM) technique to improve imaging of complex near-surface structures. DRTM uses the direct arrival as a source to forward propagate and generate source wavefields, and reversely extrapolated recorded data in a zero-lag cross-correlation imaging condition to generate the final section. The interaction between the data components during cross- correlation can use primaries and multiples to image the near-surface structure correctly. Cross-talk artifacts may exist, but they are comparatively weak.
DRTM is demonstrated on both synthetic and field data examples showing an enhanced image in areas with complex near-surface structures compared to conventional RTM imaging methods. The new algorithm can significantly enhance shallow imaging without additional computation costs compared with conventional RTM. It can produce an image with higher resolution and signal-to-noise (S/N) ratio by replacing the source wavelet with the recorded direct arrivals, which include near-surface information necessary to boost the image in areas with near-surface complexity. Since the direct arrivals are one of the most energetic events recorded, the resultant image is typically of high S/N. The wave can also illuminate shallow zones better than primaries in marine environments.
The oil and gas industry has advanced over time in terms of seismic data acquisition. From conventional data acquisition to full/wide/multi-azimuth broadband data, there is an abundance of subsurface information aimed mainly at enhancing structural resolution, for improved prospect definition. Conventional seismic imaging tends towards the higher amplitude specular/continuous part of the seismic dataset for generating reflection events. During this process amplitudes or energy related to small scale features and faults can be contaminated, therefore in order to capture that information, it is essential to preserve the wavefield while imaging.
Ishiyama, Tomohide (ADNOC Research and Innovation Center) | Ali, Mohammed (Khalifa University of Science and Technology) | Blacquiere, Gerrit (Delft University of Technology) | Nakayama, Shotaro (Delft University of Technology)
Recently, we established a generalized blending model, which can explain any methods of blended acquisition by including the encoding into the generalized operators. With this highly flexible and tolerant model, we come up with a challenging question: what it is to be, and how to find an optimal blended-acquisition design, which should be the most suitable for deblended-data reconstruction among plenty of concepts of blended acquisition. In this paper, we introduce a method of blended-acquisition encoding: temporally modulated and spatially dispersed source array, namely M-DSA, that jointly uses modulation sequencing in the time dimension and dispersed source array in the space dimension. This allows quite straightforward deblending by filtering and physically separating frequency channels in the frequency domain.
We run our blended-acquisition designing based on the deblending performance for several scenarios of blended acquisition. These examples show that: M-DSA attains the best deblending performance; this method has less constraints in the encoding with more operational flexibility, compared to other methods being developed in the industry today. Indeed, this method requires only simple signaturing in the encoding; merely frequency-banded and modulated signatures in the time dimension for each shot in the blended-source array. This could even render any other blending properties unnecessary. Those, such as distance separation among shot locations and time shifts among shot times, might not be required anymore. There might be no limitation on the number of sources, thus no limitation on the blending fold, in order to secure successful deblending. Furthermore, this method allows random sampling; randomly distributed sources in the space dimension in the blended-source array. Consequently, this method makes the blended-acquisition encoding and operations significantly simple and robust, as well as for the deblending processing. We believe that our M-DSA method should be one of the best methods of blended acquisition.
The location of passive seismic sources contains information of the physics of earthquakes/microseismic, fault systems, stress condition in reservoirs, and extent of fractures (Maxwell et al., 2010; Kamei et al., 2015). Because small earthquakes are highlighting fault/fracture locations, and such earthquakes can be related to larger events (e.g., Gutenberg-Richter law), detection, location and characterization of such small events are an important task. State-of-the-art technologies of observations are another important factor for the study of small earthquakes by producing continuous data with densely distributed seismic receivers. Detection of events in the data domain at each receiver (e.g., STA/LTA or template matching) is robust and powerful for relatively large earthquakes (Shelly et al., 2007; Zhao et al., 2010). However, for smaller earthquakes, which are hard to identify in individual observed wavefields, we need to rely on migration-based techniques to directly image and detect events (Kao and Shan, 2004). Gajewski and Tessmer (2005) showed the potential to use migration for locating passive seismic sources (time-reversal imaging). Artman et al. (2010) proposed a migration algorithm based on autocorrelation, and Nakata and Beroza (2016) extended it to crosscorrelation-based algorithm named Geometric-mean Reverse Time Migration (Gm-RTM) by treating each receiver independently.