MULTICOMPONENT SEISMIC METHODS FOR CHARACTERIZING GAS HYDRATE OCCURRENCES AND SYSTEMS IN DEEP-WATER

GULF OF MEXICO

Seth S. Haines∗, Myung W. Lee, and Timothy S. Collett U.S. Geological Survey

Denver Federal Center, Box 25046, MS 939 Denver, CO, 80225

UNITED STATES OF AMERICA

Bob A. Hardage Bureau of Economic Geology

The University of Texas at Austin Austin, TX, 78713

UNITED STATES OF AMERICA

ABSTRACT In-situ characterization and quantification of natural gas hydrate occurrences remain critical research directions, whether for energy resource, drilling hazard, or climate-related studies. Marine multicomponent seismic data provide the full seismic wavefield including partial redundancy, and provide a promising set of approaches for gas hydrate characterization. Numerous authors have demonstrated the possibilities of multicomponent data at study sites around the world. We expand on this work by investigating the utility of very densely spaced (10’s of meters) multicomponent receivers (ocean-bottom cables, OBC, or ocean-bottom seismometers, OBS) for gas hydrate studies in the Gulf of Mexico and elsewhere. Advanced processing techniques provide high-resolution compressional-wave (PP) and converted shear-wave (PS) reflection images of shallow stratigraphy, as well as P-wave and S-wave velocity estimates at each receiver position. Reflection impedance estimates can help constrain velocity and density, and thus gas hydrate saturation. Further constraint on velocity can be determined through identification of the critical angle and associated phase reversal in both PP and PS wide-angle data. We demonstrate these concepts with examples from OBC data from the northeast Green Canyon area and numerically simulated OBS data that are based on properties of known gas hydrate occurrences in the southeast (deeper water) Green Canyon area. These multicomponent data capabilities can provide a wealth of characterization and quantification information that is difficult to obtain with other geophysical methods.

Keywords: gas hydrate, seismic, OBC, OBS

∗ Corresponding author: Phone: +1 303 236 5709 Fax +1 303 236 0459 E-mail: shaines@usgs.gov

NOMENCLATURE Vp P-wave seismic velocity [m/s] Vs S-wave seismic velocity [m/s] Vz Vertical particle velocity recorded by geophone [m/s]

Vx In-line horizontal particle velocity recorded by geophone at seafloor [m/s] Vy Cross-line horizontal particle velocity recorded by geophone at seafloor [m/s] Sgh Gas hydrate saturation [%]

Proceedings of the 7th International Conference on Gas Hydrates (ICGH 2011), Edinburgh, Scotland, United Kingdom, July 17-21, 2011.

INTRODUCTION Seismic methods provide an essential and widely used set of approaches to identify and characterize gas hydrate occurrences in situ. Seismic approaches for gas hydrate characterization have progressed considerably beyond simply mapping gas hydrate accumulations via bottom simulating reflectors (BSR’s). Recent applications of seismic methods to gas hydrate characterization have included the inversion of industry-style 3D reflection data [1, 2] and the use of ocean-bottom multi-component data [3, 4, 5, 6]. Multicomponent seismic data provide recordings of the entire seismic wavefield, including shear-wave (S-wave) information that complements the compressional-wave (P-wave) information that is more commonly available. In particular, the shear velocity (Vs) can help constrain estimates of gas-hydrate saturation (Sgh) and thus can represent a valuable tool for gas hydrate studies [6, 7]. In a marine setting, multicomponent data must be collected on the seafloor because S-waves cannot propagate through the seawater. Though costly, seafloor recording offers the advantage of proximity to survey targets. Thus, P-wave (reflected P-to-P, or PP) images from ocean-bottom data may be preferable to those from sea-surface hydrophone data. In addition to PP images, seafloor multicomponent data can yield P-to-S (PS) converted wave images that complement PP images and offer sensitivity to different types of interfaces. Seismic anisotropy, evidenced by S-wave splitting, can also be characterized with multicomponent data, providing an improved understanding of fractures and other features related to the total gas/gas hydrate system [8, 9]. Ocean-bottom seismometers (OBS, shown in Figure 1) are self-contained devices that record four components of seismic data: a hydrophone records pressure and a three-component geophone records Vx, Vy, and Vz ground motion. Until recently, OBS have typically been dropped to the seafloor from the survey vessel and then acoustically released from their seafloor anchor at the end of the recording time such that they float to the surface where they are recovered. Recording with OBS can provide reflection and refraction data that yield images along with Vp and Vs velocity models suitable for estimation of

Sgh [7, 10]. Such surveys typically employ up to a few 10’s of OBS which are deployed at spacings of several hundred meters or more.

Figure 1: Ocean-bottom seismic data are generally recorded with either ocean-bottom seismometer (OBS) or ocean-bottom cable (OBC) technology. Modern, industry-style, ocean-bottom seismic acquisition typically employs closely spaced receivers, with spacings of 10’s of meters to a couple of hundred meters. This may be accomplished using ocean-bottom cables (OBC, as shown in Figure 1) that contain hundreds of 4-component receivers at a fixed spacing, or it may be accomplished using 100’s or even 1000’s of OBS deployed in dense arrays by a remotely operated vehicle (ROV). Such acquisition is often conducted in a grid on the seafloor to yield 3D data that include full P-wave and converted PS wave information for reflection/conversion processing and velocity analysis. Due to technical limitations, OBC acquisition is generally not conducted in water depths greater than 1 km; therefore OBS are the only viable multicomponent option for deep-water gas hydrate targets. Using modern OBS techniques and equipment can yield tremendously valuable data, however such surveys tend to carry a hefty price tag due to the cost of ROV use. In this work, we focus on the benefits that modern multicomponent seismic methods can bring to gas hydrate studies, and describe emerging data processing techniques that can maximize the value of such data while minimizing survey cost. Our objective is to demonstrate these concepts on existing OBC data and realistic synthetic ocean-bottom data to highlight the value of collecting dedicated industry-style multicomponent seismic data at established gas hydrate study sites.

PROCESSING DATA FOR REFLECTION IMAGES AND VELOCITY Traditional, industry-style data processing for ocean-bottom seismic data consists of sorting by mid-point location and stacking and/or migrating, much like for ordinary marine hydrophone cable data or terrestrial data. Backus et al. [5] propose an alternative approach for processing ocean-bottom data, designed to yield high-resolution PP and PS images of near-seafloor targets such as gas hydrate accumulations. This approach is similar to that typically used for processing vertical seismic profile (VSP) data, and is centered on the concept of processing the data from each receiver location independently of the other receiver locations. Example ocean-bottom cable data We illustrate several data-processing approaches with a segment of ocean-bottom cable data collected in approximately 800 m water depth in the Green Canyon area of the Gulf of Mexico. This is a 4-km cable, with 25 m receiver group spacings for 160 total receiver locations. Airgun seismic source locations are spaced at 50-m intervals at the sea surface.

Figure 2: Data recorded by each of the four

receiver components at one receiver location on an OBC. The first sea-surface multiple is labeled

“M”. The four components of data from one receiver location are shown in Figure 2. The plotted data correspond with 160 shots spread over 8 km. The pressure and Vz components show similar features, such as the reverberatory down-going airgun bubble pulse and the up-going PP reflections from sub-seafloor layers. The Vx

component shows some features similar to the Vz component, but is dominated by up-going PS converted arrivals from sub-seafloor layers. The Vy component records limited energy, because the airgun source (located in-line with the OBC) creates little vibration transverse to the OBC. Processing for PP reflection images and for Vp For the purposes of PP reflection imaging, we must isolate the up-going reflected P-wave arrivals. The partial redundancy provided by the four recorded data components is critical to this operation. The pressure and Vz components record the down-going wavefield with the same polarity and the up-going wavefield with opposite polarity. Thus the down-going and up-going wavefields may be separated by summing or differencing (respectively) these two data components [5], with results for one receiver location shown in Figure 3.

Figure 3: Down-going P wavefield (left), and up-going P (middle) and S (right) wavefields for one

receiver location along the OBC. Prior to up/down wavefield separation, the data must be calibrated to account for different sensor responses between the pressure and Vz components; this calibration is essential for accurate wavefield separation. The goal of this calibration is to adjust the Vz data (recorded by the geophone) so that they have the same frequency response as the pressure data (recorded by the hydrophone). For this purpose, Backus et al. [5] propose an approach involving analysis of long-offset refraction data. Haines et al. [11] propose a median-filter-based approach as an alternative that does not require long offset data. In addition to calibration, the amplitude of the Vz data must be corrected for the incidence angle of the direct seismic waves; this is accomplished with division by the cosine of the incidence angle. Following wavefield separation, the down-going wavefield is deconvolved from the up-going

wavefield to yield the PP reflectivity. These processing steps are conducted separately for each receiver location, yielding PP reflectivity for each; these gathers may then be used to construct stacked sections. Due to typical seismic velocities and typical recording geometries, reflection raypaths approach vertical even for a range of offsets. Thus an image may be constructed by including the handful of traces from each receiver location that covers the area beneath that location; an image made in this manner is shown in Figure 4.

Figure 4: Simple reflection images for PP

reflections (above) and PS converted arrivals (below).

The PP reflectivity gathers may also be analyzed to determine Vp with high resolution. Backus et al. [5] suggest a ray-tracing based approach instead of traditional move-out analysis because it has proven to yield greater accuracy for these near-seafloor targets where the geometry and velocities do not conform to the assumptions inherent in moveout correction. They demonstrate sensitivity of 0.5% with high depth resolution. Processing for PS reflection images and for Vs The processing approach for PS is similar to that for PP data, beginning with separation of the up-

and down-going wavefields. The up-going PS wavefield is determined by combining the Vx and pressure components to remove the up-going PP reflections and provide the PS conversions. The result for one receiver location in shown in Figure 3. Following deconvolution by the down-going P wavefield, the PS gather is used for velocity analysis and image creation. The raypaths of PS energy for any particular receiver location are nearly vertical beneath that receiver, due to the very high Vp/Vs ratio of these deep-water, near-seafloor, sediments. Thus each receiver location only provides one trace for images such as the simple image shown in Figure 4. As for Vp, ray tracing provides high-precision Vs models. By coordinating Vp and Vs model development with image registration (identifying common interfaces in the PP and PS images) it is possible to construct a self-consistent, high precision, velocity model for both Vp and Vs [12]. These velocities are suitable for gas hydrate saturation estimation and other analyses. IMPROVING RAY COVERAGE The formidable cost of acquiring seafloor seismic data generally results in acquisition geometries that are less dense than might be desirable, or that cover a smaller area than would be ideal. The negative impact of such sparse geometries is particularly apparent for shallow sub-seafloor layers, which are precisely the targets of interest in gas hydrate studies. Two emerging data processing approaches offer the potential for improved ray coverage for any given dataset. Interferometric processing It has been known for several decades that the crosscorrelation of seismic records recorded by two stations results in data comparable to what would be recorded by one of those receivers if the other was a seismic source [13]. This concept has been advanced considerably in recent years, and broadened to include passive and active seismic data, as well as a range of processing variations. These methods are broadly referred to as “interferometric”, and are thoroughly reviewed by Wapenaar et al. [14, 15]. Of particular interest is the virtual-source method proposed by [16], which deals with re-datuming active-source data. By crosscorrrelating receiver gathers and summing across the source domain it

is possible to create data representing virtual seismic sources at the locations of true receivers. By crosscorrelating particular parts of the true recorded seismic wavefield it is possible to preferentially select for desired characteristics in the virtual wavefield. For the case of ocean-bottom seismic data, this implies that we can create, through interferometric processing of airgun data, virtual data that represent seismic experiments that employ seafloor sources of any chosen orientation or any chosen wavefield, and receivers that are sensitive to specific orientations or wavefields. The one caveat is that the real data must contain the wavefields of interest; for example we cannot hope to use interferometry to create images of pure shear (SS) reflections because the true data contain very minimal down-going S-wave energy.

Figure 5: Receiver gathers for PP (left) and (PS) right, constructed through interferometry.

The separated up- and down-going wavefields, described previously, provide an ideal starting point for interferometric processing. Using them, we are able to virtually conduct a seismic survey with seismic sources at the seafloor that have the exact (known) downward propagating P-wavefield and co-located seismic receivers that specifically record the known up-going P or PS wavefield. Receiver gathers determined through this processing approach are shown in Figure 5. These gathers correspond with a virtual seismic source at one of the true receiver locations, and virtual receivers at the locations of all the true receivers. These PP and PS interferometric gathers are both rich in reflectivity and ready for velocity analysis or image construction. In addition to the re-datumed source locations, a key feature of these gathers is that the mid-point spacing of adjacent

traces is half of what it was in the original data; these data correspond with a source and receiver spacing of 25 m whereas the original OBC data have a source spacing of 50 m and a receiver spacing of 25 m. Simple reflection images constructed from interferometric processing are shown in Figure 6. Both interferometric images show similar features to the images shown in Figure 4. Given that these interferometric results are early efforts, they are quite encouraging. The re-datuming is successful, and we have achieved denser ray coverage with the same survey geometry. Clearly the PP image in particular shows the need for improvement; it shows abundant low frequency energy but limited higher frequencies and thus reduced resolution. The PS image rivals the more conventional result, and may show improved reflectivity in some areas (for example, the zone around 0.5 seconds, at positions greater than 3000 m). Both of the PS images (Figures 4 and 6) show the strong reverberatory character that is present in the raw data for positions between 0 m and approximately 1700 m.

Figure 6: PP (top) and PS (bottom) images created through interferometric processing.

Imaging with down-going seismic energy Nearly all traditional seismic reflection processing techniques include only the seismic energy that has propagated downward from the source and been reflected upward at subsurface interfaces. The actual recorded seismic wavefield, however, includes a wealth of other raypaths, such as the energy that reflects multiple times at a given interface and has multiple up- and down-going legs. Often considered an annoyance, and sometimes a major impediment to target imaging, these multiple arrivals can be used to create improved seismic images with improved target illumination. The “P mirror” technique, described by Ronen et al., is a simple approach that yields improved PP images from ocean-bottom data [17]. By exploiting rays that reflect downward at the sea surface, which can be considered to be a perfect reflector, it is possible to achieve broader reflection point coverage and improved imaging as shown in Figure 7. Such methods have been shown to yield considerable improvement over conventional approaches [17, 18]. Unfortunately, a directly analogous PS version of the P-mirror technique is not possible because the extra “leg” of the seismic ray path used for the imaging occurs in the seawater where shear waves cannot propagate. Though other multiply reflected waves do include desirable S-wave energy, a PS version of the P-mirror method is not readily available.

Figure 7: Conventional PP reflection raypaths recorded by an OBS (left), and multiple reflections

used in mirror imaging of PP data (right). OTHER PHYSICAL PROPERTY ESTIMATION APPROACHES A key objective of many gas hydrate studies is to estimate physical properties of hydrate-bearing sediments or of other sediments that may be involved with the total gas/gas hydrate system.

For the task of quantifying in-situ gas hydrate, estimates of gas hydrate saturation are essential; these estimates require precise seismic velocity measurement. For the purpose of understanding the total gas system, the presence and character of fractures must be studied; seismic anisotropy can be a valuable characterization tool. Complementing the approaches mentioned earlier, are a variety of other techniques that exploit the unique characteristics of ocean-bottom seismic data to provide valuable physical property information. We focus on exploitation of opportunities involving readily available, long-offset recordings. Critical angle observations Seismic reflection amplitude varies with the incidence angle of the causal wave, and these relations have long been used to estimate material properties and hydrocarbon quantities. Such methods, however, tend to exploit only a relatively narrow range of incidence angles due to the limited source-receiver offset range available in most seismic surveys (approximately 0-20 degrees). Ocean-bottom data afford the opportunity to study a much larger range of incidence angles because the receivers are located very near to the survey targets. With incidence angles up to 60 or more degrees, we can potentially observe the phase and amplitude transitions that occur at the critical angle of reflection and further constrain seismic velocity and gas hydrate saturation. The critical angle is the incidence angle beyond which the reflection amplitude increases dramatically (for interfaces with increasing velocity), and beyond which the reflection typically begins to show reversed polarity (opposite phase). We focus now on the Green Canyon 955 block that has been studied in detail by the Gulf of Mexico Gas Hydrate Joint Industry Project (JIP) [19, 20]. At this site, high gas hydrate saturations have been indicated by drilling and seismic data [19]. Figure 8 shows reflection amplitude versus incidence angle for an interface of shale over hydrate-bearing sand. Using the standard Zoeppritz relations, these calculations are based on material properties (Table 1) approximating those found at GC955 in the Gulf of Mexico, and based on the relations provided by Lee [21]. These

calculations assume plane-wave propagation, which is unrealistic but not grossly erroneous for typical ocean-bottom data collection geometries.

Figure 8: Relation between reflection coefficient and incidence angle for a shale-over-hydrate-bearing-sand interface (at left) and the relation

between critical angle and gas hyrate saturation (at right).

Lithology Sgh

(%) Vp

(m/s) Vs

(m/s) Density (g/cm3)

Shale 0 1800 460 1.960 Sand 0 1850 550 1.952 Sand 20 2010 640 1.946 Sand 40 2220 760 1.941 Sand 50 2340 840 1.937 Sand 60 2490 930 1.934 Sand 70 2670 1050 1.931 Sand 80 2900 1210 1.928

Table 1. Physical properties used in simulations

and analytic calculations, based on the theory of Lee [21].

Seismic velocities from the GC955H well are plotted in Figure 9, and numerically simulated data based on these velocities (the solid Vp and Vs lines shown in Figure 9) are plotted in Figure 10. Numerical simulations were created using the code e3d that is described by Larsen [22]. For this simulation the model consists of a water layer overlying a half-space with velocity gradients as indicated in Figure 9 and an embedded layer of gas-hydrate-bearing sand at 413 m depth below seafloor. Velocities do not vary laterally in this simple model. The seismic source simulates an airgun at the sea surface and the plotted data are Vz component data that would be recorded by a sensor at the seafloor. Using ray-tracing

techniques we can determine the incidence angle for each trace; approximate incidence angles are indicated in Figure 10. The seismic data show two prominent arrivals. First, arriving at approximately 1.2 s at 0-m offset, is the direct arrival. Second, arriving at approximately 1.7 s at 0-m offset, is the reflection from the hydrate-bearing-sand. This arrival is actually two reflections, from the top and bottom of the layer, as can be seen more clearly in the lower, zoomed-in, plot. These synthetic data exhibit an abrupt increase in amplitude in the reflection from the top of the sand that occurs at an incidence angle of approximately 30 degrees. At longer offsets the reflection from the lower boundary of the sand disappears and we observe that the reflection from the upper boundary shows reversed polarity. Looking at the plotted horizontal axes on Figure 10, it can be seen that we can expect to achieve incidence angles up to at least 60 degrees and as high as 75 or more degrees for this data acquisition location and for realistic acquisition geometries. Thus we can expect to observe critical-angle and post-critical PP reflections for gas hydrate saturations as low as 20% depending on data quality and other factors.

Figure 9: GC955H seismic velocities. Plotted Vp (thin dashed blue line) is measured by the sonic log, and Vs (thin dashed red line) is estimated from the Vp log. Solid lines are the simplified

model used for synthetic data.

In order to understand the sensitivity of critical angle analysis, we have calculated numerical simulations for a range of gas hydrate saturations. The synthetic data for reflections from these shale-over-hydrate-bearing-sand interfaces are plotted in

Figure 11. The reflections have been flattened and windowed for simplicity. The variation in critical angle with saturation is clearly visible for these data, and we suggest that visual inspection of such data would be able to distinguish critical angle (and saturation) differences of approximately those plotted here. That is, if data quality is suitable for the necessary offsets, we can hope to identify critical angles with uncertainty of no more than +/- 5 degrees. This would provide constraint on Sgh with uncertainty of approximately 10%.

Figure 10: A synthetic receiver gather for ocean-bottom data, based on the simplified GC955H

velocity model shown as the solid line in Figure 9. In the lower plot, the reflection from the hydrate-bearing sand has been windowed, and flattened

with normal-moveout correction. The horizontal range is the same in both plots, but the

approximate incidence angle is indicated in the lower plot. The simulated data show some

modeling artifacts such as the reflections from the sides of the model space, visible as sharply

dipping energy in the lower plot.

Figure 11: Windowed, flattened, reflection events

for the upper surface of a hydrate-bearing sand below a shale, with properties as shown in Table 1. DISCUSSION AND CONCLUSIONS Multicomponent seismic data have shown great utility in gas hydrate studies, and demonstrate greater potential for future studies through the adoption of modern industry techniques. Through a variety of approaches, we can determine Vp and Vs velocity properties with fine spatial resolution and high precision. This information is available over a greater area, and with denser spacing, than was previously possible due to emerging acquisition and processing approaches. Together, this set of techniques provides a powerful tool for gas hydrate characterization. REFERENCES [1] Lee MW, Collett TS, Inks TL. Seismic-attribute analysis for gas-hydrate and free-gas prospects on the North Slope of Alaska. In: Collett T, Johnson A, Knapp C, Boswell R, editors. Natural gas hydrates—Energy resource potential and associated geologic hazards: AAPG Memoir 89, 2009. p.541-554. [2] Dutta NC, Utrech, RW, Shelander D. Role of 3D seismic for quantitative shallow hazard assessment in deepwater sediments. The Leading Edge 2010:29(8): 930-942. [3] Andreassen K, Berteussen KA, Sognnes H, Henneberg K, Langhammer J, Mienert J. Multicomponent ocean bottom cable data in gas

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[13] Claerbout JF. Synthesis of a layered medium from its acoustic transmission response. Geophysics 1968:33(2):264-269. [14] Wapenaar K, Draganov D, Snieder R, Campman X, Verdel A. Tutorial on seismic interferometry. Part 1: Basic principles and applications. Geophysics 2010:75(5):75A195-75A209. [15] Wapenaar K, Slob E, Snieder R, Curtis A. Tutorial on seismic interferometry. Part 2: Underlying theory. Geophysics 2010:75(5):75A211-75A227. [16] Bakulin A, Calvert R, The Virtual source method: Theory and case study. Geophysics 2006:71(4):SI139-SI150. [17] Ronen SL, Comeaux L, Miao JG. Imaging downgoing waves from ocean bottom stations. In: Proceedings of the 75th Annual Meeting of the Society of Exploration Geophysicists, Houston, 2005. [18] Dash R, Spence G, Hyndman R, Grion S, Wang Y, Ronen S. Wide-area imaging from OBS multiples. Geophysics 2009:74(6):Q41-Q47. [19] Boswell R, Collett T, Frye M, McConnell D, Shedd W, Dufrene R, Godfriaux P, Mrozewski S, Guerin G, Cook A. Gulf of Mexico Gas Hydrate Joint Industry Project Leg II: Technical Summary. 2009. http://www.netl.doe.gov/technologies/oil-gas/publications/Hydrates/2009Reports/TechSum.pdf [20] McConnell D, Boswell R, Collett T, Frye M, Shedd W, Guerin G, Cook A, Mrozewski S, Dufrene R, Godfriaux P. Gulf of Mexico Gas Hydrate Joint Industry Project Leg II: Green Canyon 955 site summary. 2009. http://www.netl.doe.gov/technologies/oil-gas/publications/Hydrates/2009Reports/GC955SiteSum.pdf [21] Lee MW. Models for gas hydrate-bearing sediments inferred from hydraulic permeability and elastic velocities, U.S. Geological Survey Scientific Investigations Report 2008–5219. U.S. Geological Survey, 2008. [22] Larsen S, Grieger J. Elastic modeling initiative, Part III: 3-D computational modeling. In: Proceedings of the 68th Annual Meeting of the Society of Exploration Geophysicists, New Orleans, 1998. ACKNOWLEDGEMENTS We are grateful to Paul Murray for his substantial contributions toward data access and for developing the code used for some of the data

processing. We thank WesternGeco for permission to publish images from their OBC dataset. Financial support has been provided by Department of Energy – U.S. Geological Survey Interagency Agreement DE-A126-05NT42496 and by the U.S. Geological Survey Energy Resources Program.