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PSGas Hydrate Geohazard Assessment in the Northern Gulf of Mexico Using a Vertical Line Array*

By

Erika Géresi 1, N.R. Chapman 1, T.M. McGee 2, and J.R. Woolsey 2

Search and Discovery Article #40159 (2005)

Posted July 25, 2005

 

*Poster presentation at AAPG Annual Convention, with SEPM, Calgary, Alberta, June 19-22, 2005.

Click to view poster in PDF format (2.3MB).
Right click, then click "Save Target As . . ." to download poster to hard drive (21.5 MB).

1School of Earth and Ocean Sciences, University of Victoria, Victoria, BC Canada ( [email protected] )

2MMRI/CMRET, University of Mississippi, Oxford, MS USA

 

Abstract

In order to understand the consequences and causes of sea-floor instability in the presence of gas hydrate, it is imperative to understand the geological setting and the physical properties of the hydrates, and to be able to estimate the distribution and concentration of the gas hydrate deposits. Conventional seismic techniques often fail to image the complex geological features, especially around and under salt domes or gas hydrates, which have high Previous HitpropagationNext Hit velocities for seismic waves. Therefore, new techniques in data acquisition and processing are sought to improve the image of complex areas, especially in the presence of gas hydrate.

This paper reports the progress in processing and development of a remote, multi-sensor sea-floor station planned for the continental slope of the northern Gulf of Mexico to monitor changes in the shallow sub-bottom over an extended period of time. A set of experiments with a prototype Vertical Line Array (VLA) were carried out as part of the development. VLA, multi- and single-channel reflection seismic data were collected from Mississippi Canyon (MC798) (800m) and Atwater Valley Area (AT14) (1300m). This research project integrated these datasets in order to assess potential geohazards such as gas hydrates using Previous HitpropagationNext Hit velocities, physical properties and the acoustic character of the sub-bottom.

An inversion approach was developed using (1) travel-times obtained from the tau-p transform of Vertical Cable common receiver gathers, and (2) amplitude versus offset data to determine velocities, dips and depths. The processing result of VLA data showed improved vertical resolution and better reflectivity contrast. The physical properties of the sub-bottom estimated from the inversions and interpretation made possible a more advanced assessment of the nature and distribution of potential geohazards such as gas hydrate at the study areas.

 

 

 

uAbstract

uIntroduction

uGas Hydrate

  uHazard

  uClimate

uSea-Floor Stability

uVLA Acquisition Technique

uTravel-Time Inversion

uVLA Processing

  uInterval Velocity Analysis

  uMigration Velocity Analysis & PSDM

uAmplitude vs. Offset (AVO)

uInversion Technique

uConclusion

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uIntroduction

uGas Hydrate

  uHazard

  uClimate

uSea-Floor Stability

uVLA Acquisition Technique

uTravel-Time Inversion

uVLA Processing

  uInterval Velocity Analysis

  uMigration Velocity Analysis & PSDM

uAmplitude vs. Offset (AVO)

uInversion Technique

uConclusion

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uIntroduction

uGas Hydrate

  uHazard

  uClimate

uSea-Floor Stability

uVLA Acquisition Technique

uTravel-Time Inversion

uVLA Processing

  uInterval Velocity Analysis

  uMigration Velocity Analysis & PSDM

uAmplitude vs. Offset (AVO)

uInversion Technique

uConclusion

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uIntroduction

uGas Hydrate

  uHazard

  uClimate

uSea-Floor Stability

uVLA Acquisition Technique

uTravel-Time Inversion

uVLA Processing

  uInterval Velocity Analysis

  uMigration Velocity Analysis & PSDM

uAmplitude vs. Offset (AVO)

uInversion Technique

uConclusion

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uIntroduction

uGas Hydrate

  uHazard

  uClimate

uSea-Floor Stability

uVLA Acquisition Technique

uTravel-Time Inversion

uVLA Processing

  uInterval Velocity Analysis

  uMigration Velocity Analysis & PSDM

uAmplitude vs. Offset (AVO)

uInversion Technique

uConclusion

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uIntroduction

uGas Hydrate

  uHazard

  uClimate

uSea-Floor Stability

uVLA Acquisition Technique

uTravel-Time Inversion

uVLA Processing

  uInterval Velocity Analysis

  uMigration Velocity Analysis & PSDM

uAmplitude vs. Offset (AVO)

uInversion Technique

uConclusion

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

uAbstract

uIntroduction

uGas Hydrate

  uHazard

  uClimate

uSea-Floor Stability

uVLA Acquisition Technique

uTravel-Time Inversion

uVLA Processing

  uInterval Velocity Analysis

  uMigration Velocity Analysis & PSDM

uAmplitude vs. Offset (AVO)

uInversion Technique

uConclusion

Figure Captions

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Introduction

The conventional seismic techniques often fail to image the complex geological features, especially around and under salt domes and sills or in the presence of gas hydrates that have high Previous HitpropagationNext Hit velocities for seismic waves. The conventional 3-D marine seismic survey generally acquires several 2-D lines over the target area. The source vessel pulls the streamer carrying receivers positioned on the same line where the source is activated. Thus, source-receiver azimuths follow the direction of those 2-D lines. This means that all the energy spread away from the 2-D profile is missed. Missing energy is responsible for the lack of illumination in most targets under complex geology. Therefore, new techniques in data acquisition and processing are sought to improve the image of complex areas.

One of the new seismic data acquisition techniques is the vertical cable (VLA). In comparison with the conventional method, the VLA provides advantages such as flexibility during operation to cover the surveyed area, recording the signal in a quieter environment, and an opportunity for direct separation of up-coming and down-going Previous HitwaveNext Hit fields.

However, with the unconventional acquisition geometry, the VLA data can not be treated directly by the conventional procedures of seismic data processing. The CMP technique is no longer applied. Therefore, new algorithms had to be created. In this research, a series of algorithms were created to achieve the best interpretable seismic image from the VLA data and also to have the most information of the physical properties. The advantages of the different acquisition geometry were taken into account.

The processing results indicated complex geological settings and velocities that could be attributed to seafloor methane hydrate accumulations.

 

Gas Hydrate

Gas hydrate is a solid, ice-like substance containing natural gas -mostly methane and water. Gas hydrates occur offshore on continental margins where nutrient-rich waters deliver organic detritus for bacteria to convert to methane and, to a lesser extent, in the permafrost sediments of Polar Regions. Most marine hydrates are stable at the relatively low temperatures and high pressures found in sediments at water depths about 500 meters. The sediment interval in which gas hydrates occur is known as the gas hydrate stability zone (GHSZ). Below and above this zone free natural gas may exist. Large accumulations of gas hydrates have been identified the US eastern seaboard, the Pacific Northwest, Japan etc. The presence of gas hydrate can be inferred from seismic evidence such as bottom simulating reflectors (BSRs) or changes in seismic velocity (e.g., Hovland and Judd, 1988. The petroliferous northern Gulf of Mexico is noted for its obvious absence of BSR’s, a characteristic it shares with other ”active” passive margins with mobile salt and/or shale.

Hazard

Gas hydrates may pose a geohazard in coastal areas because the dissociation, or melting, of solid gas hydrate to water and gas result in slope instability that can trigger large submarine landslides and even tsunamis. Similarly, as natural gas and oil exploration moves into deeper water where gas hydrate deposits are more likely, such as the deepwater Gulf of Mexico, drilling operations may cause gas hydrate melting, sediment instability, borehole collapse and gas blowouts.

Climate

Methane, an important green house gas, released from gas hydrate in marine sediments may contribute to global warming.

 

Gulf of Mexico Sea-Floor Stability

In the Gulf of Mexico, gas hydrate mounds form along the intersections of faults with the sea floor. They are edifices largely constructed of water from the sea and hydrocarbon gases that have migrated up the faults from buried reservoirs. In addition to gas hydrates, they also contain various minerals deposited by bacteria feeding on the hydrocarbons. The mounds are ephemeral, capable of changing greatly within a matter of days. Many geoscientists familiar with recent geologic processes in the Gulf of Mexico think that events which cause changes to the hydrate mounds also trigger episodes of sea- floor instability.

Hydrates contained in sediments are stable as long as the sediments are within the hydrate stability zone (HSZ) as defined by pressure, temperature and chemical composition. If hydrocarbon gases migrating up faults encounter sediments of sufficient permeability that lie within the HSZ, hydrates can form within the pore spaces and support the sediment frame. This increases the sediment’s shear modulus and thereby its bearing capacity.

Common indicators of bearing capacity are the speeds at which compressional (P) and shear (S) waves propagate below the sea floor and the efficiency of P-to-S conversion (PS) at reflecting horizons. A comprehensive monitoring station would be capable of measuring these and many other parameters that are relevant to the formation and dissociation of gas hydrate. The general configuration of the hydrate stability zone in MC798 has been observed seismically and, in light of the heat-flow data, its thickness estimated to be about 400m (Trevor Lewis, pers.com.). The negative reflection about 500ms below the sea floor is interpreted as the base of the hydrate stability zone.

 

Vertical Line Array (VLA) Acquisition Technique

A prototype VLA has been designed and constructed as part of the development leading to deploying a remote, multi-sensor sea-floor station planned for the continental slope of the northern Gulf of Mexico. The station will use one VLA and four horizontal arrays of hydrophones to monitor changes in the shallow sub-sea-bottom over an extended period of time. The prototype Vertical Line Array (VLA) was deployed and recovered successfully in 2002 and 2003 by the CMRET.

During the 2002 and 2003 VLA deployments, survey tracks were carries out while firing a surface-towed 80 in3 watergun. In 2002, surface source deep receiver single channel reflection data were also recorded.

 

Travel-Time Inversion for Vertical Cable Geometry

The basic unit of processing in the VLA technique is the common-receiver gather (CRG) which consists of one single selected receiver in the cable and shots distributed regularly over the surveyed area. The common midpoint (CMP) technique is not appropriate anymore. Therefore, the travel-time equation needs to be revisited to study procedures to obtain interval velocities and depths directly from the vertical cable data.

An analytic proof for the 2-D travel-time equation was developed using horizontal and vertical slowness for models with dipping interfaces and homogeneous layers. Travel-time curves in both τ - p and T - X domains were computed as well as the ray path for vertical cable geometry.

 

VLA Processing Development and Results

This new method deploys hydrophones attached to a vertical cable that was anchored to the sea floor. Once the cable was deployed a source boat with a watergun fired in a large surface grid over the cable. With this unconventional acquisition geometry, the vertical cable cannot be treated directly by the conventional procedures of seismic data processing. Therefore, new algorithms had to be created.

The procedure that was developed for processing the MC798 VLA dataset:

  • Reformating

  • Geometry Setup

  • Positioning

  • Ray Tracing

  • Common Receiver Gather ”Sorting

  • Static Correction

  • Detrending

  • Direct Previous HitWaveNext Hit Information ( Deterministic Deconvolution/ Phase Conjugation)

  • Interval Velocity Analysis

  • NMO Correction

  • Spherical Divergence Correction

  • Migration Velocity Analysis

  • Pre-stack Depth Migration (PSDM)

Each step had to be programmed individually taking into account the special geometry of the VLA.

Interval Velocity Analysis

Interval velocity analysis was applied and the calculated velocity was used in the normal moveout correction. A commercial software (Claritas) was used at this time to achieve the desired interval velocities.

Migration Velocity Analysis and Pre-stack Depth Migration (PSDM)

The pre-stack depth migration generates images of all reflection points which are ruled by the macro-velocity model, the geometry of cables, and shots at the surface. The entire image of one surveyed area is the stack of the images of every common-receiver gather of all cables involved in that particular area. The principle of reciprocity says that these data are equivalent to a single source (in place of one receiver in the cable) with receivers at the surface. Therefore, a shot-record migration scheme could be applied to these data. Shot-record migration requires back Previous HitpropagationNext Hit of the receiver field and forward Previous HitpropagationNext Hit of the source Previous HitwaveNext Hit field [Berkhout (1980)]. Thus, assuming reciprocity, common-receiver gather migration shots are back propagated and receivers are forward propagated.

Claerbout (1985) suggests that reflectors exist in the earth where the onset of the back propagated Previous HitwaveNext Hit-field is time coincident with the forward propagated Previous HitwaveNext Hit- field. Both Previous HitwaveNext Hit fields must be extrapolated. Downward continuation of the source field can be handled by any Previous HitwaveTop equation method [Berkhout (1980), Claerbout (1985), Gazdag and Saguazzero (1984).

The images of both fields are important to complete the image of the sub-surface. The improvement is not just to increase the signal-to-noise ratio as different receivers in the cables do but also to bring different illumination from the sub-surface structure to contribute for the final image.

 

Amplitude vs. Offset (AVO) Modeling/Inversion

Amplitude versus offset (AVO) is an important tool in sediment classification and hydrocarbon exploration based on measuring reflection coefficient of acoustic or seismic waves at an interface as a function of the angle of incidence (referred as AVO function). The goal is to determine a model of the physical parameter at the interface by inverting the measured reflectivities. The inverse problem is functionally nonlinear and inherently nonunique; hence, an important component involves estimating the uncertainties (probabilities) of the recovered model parameters.

AVO modeling plays an active role in three areas: new technology development, quality control (QC) data processing, and assisting data interpretation. Calibration on common receiver gathers and output AVO attributes can be conducted for optimizing AVO processing. It helps to answer the questions such as: whether the CRGs are properly processed with an amplitude friendly processing flow and parameters: whether phase, tuning, signal-to-noise ratio and other factors are influencing the solutions: and whether the correct impedance background is used in elastic rock property inversion.

 

Inversion Technique

In this work, an inversion approach was applied to infer seabed geoacoustic parameters that emphasize estimates for parameter uncertainties. This approach is based on Bayesian inference theory, which characterizes the solution to an inverse problem in terms of its posterior probability density (PPD). The PPD combines prior information about the model, such as parameter upper and lower bounds, with the information provided by an observed data set, quantified in term of the likelihood function defined by the statistical distribution of the data errors. The multi-dimensional PPD is typically interpreted in terms of its moments, such as the posterior mean, covariance, and marginal distribution, which provide parameter estimates and uncertainties. Determining these properties requires estimating multi-dimensional integrals of the PPD using sampling methods such as Monte Carlo integration or importance sampling. Meaningful estimation of PPD moments requires an unbiased sampling algorithm with the rigorous convergence criterion.

An important aspect of Bayesian inversion for measured data involves estimating data uncertainties, including both measurement and theory errors, which is carried out here using a maximum-likelihood approach.

This method has also been used as a quality control tool on the amplitude preserving processing for the amplitude vs. offset investigation.

 

Conclusion

The gas hydrate stability zone in MC798 has been indicated by the heat-flow data and its thickness estimated to be about 400m (Trevor Lewis, pers.com.). The negative reflection about 500ms below the sea floor is interpreted as the base of the hydrate stability zone. However, modeling and imaging this zone was problematical. Therefore, new method needed to be tried. The Vertical Line Array, which is part of the development leading to the Gas Hydrate Monitoring Station in the northern Gulf of Mexico, was deployed first time at hazardous sites such as MC798 and AT14. The goal was to find a seismic/acoustic technique to successfully image the GHSZ and to retrieve more information from the acoustic properties of this zone. The used methods all tried to take advantage of the uniqueness of the acquisition geometry.

The velocity models were created both using conventional seismic techniques such as interval velocity and migration velocity analysis and an ocean acoustical inversion technique to get the acoustic characteristic and parameters of the sediments. Bayesian Inversion approach was applied to provide estimates and uncertainties of the viscoelastic physical parameters at an interface.

The inversion was based on Gibbs sampling approach to determine properties of the posteriori probability distributions (PPDs). It was an excellent quality control tool on the amplitude preserving processing results itself as well that is a crucial element of the successful AVO inversion/modeling/analysis.

The results clearly show the potentials of these combined methods to assess potential geohazards such as gas hydrates at the target areas or detect any changes in the sub-surface.

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