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Resolving intrinsic and extrinsic components of seismic attenuation: benefits for reinterpreting deep crustal structure in North Sea seismic archives

Dr Roger Clark (SEE), Dr Adam Booth (SEE), Dr Douglas Paton (SEE)

Project partner(s): TGS (CASE)

Contact email: r.a.clark@leeds.ac.uk

The Palaeozoic and Mesozoic basins of the North Sea have for decades been the focus of significant seismic reflection interest.  The hydrocarbon prospectivity of the region, coupled with the varying structural styles of hydrocarbon-bearing structure, has prompted significant development of novel seismic acquisition, processing and interpretation techniques.  While hydrocarbon basins are the priority targets of these acquisitions, there is the potential to reprocess and reinterpret them to reveal deep crustal structure (e.g., England and Soper, 1997).  However, for such interpretations to be possible, significant effort is required to boost signal-to-noise ratio.  A major component of seismic signal loss is the process of frequency-dependent attenuation.  This project is a study of the methods by which attenuation mechanisms are manifest in seismic data, and how they are based compensated, to facilitate enhanced seismic interpretation across the whole depth range of the recorded archive.

Frequency-dependent attenuation, quantified by the Quality Factor Q, arises because subsurface materials are imperfectly elastic: an amount of the elastic wave energy is lost as the wave propagates: the wave is ‘damped’.  While methods for measuring attenuation are well-established (e.g., Reine et al., 2012), the quality factor expressed in seismic data is a combination of intrinsic and extrinsic effects.  Intrinsic effects include the conversion of seismic energy to heat across grain boundaries that are loosely-bonded or fractured, and the intra-pore fluid flow that occurs as the seismic wavelet propagates; extrinsic effects include the interference of the wavelets at between closely-spaced reflective interfaces.  Intrinsic and extrinsic effects are difficult to separate (e.g., Mangriotis et al., 2013) using just one survey type, but for meaningful Q results as a rock property, and for robust Q-compensation and improvement of signal-to-noise ratio (e.g., Figure 2), an assessment must be made of the relative contribution of intrinsic and extrinsic attenuation mechanisms. 

Figure 1. Distribution of seismic quality factor, Q, in a North Sea seismic line.  Measured Q trends clearly correlate with key horizons, but there is no distinction between intrinsic and extrinsic Q effects (Woods, 2016).

 Industry partners TGS have very recently developed a tool for semi-automated estimation of measured Q from post-stack seismic reflection data: it shows considerable promise (Figure 1) and now merits refining.  Furthermore, estimates of extrinsic attenuation can be made from well log analysis (e.g., Shapiro and Zien, 1993), allowing these Q estimates to be validated.  TGS are ideally placed to collaborate in this project, because you will work with TGS’s extensive North Sea 2D marine seismic archive (Figure 3), and also their associated comprehensive suite of borehole logs – thereby facilitating, for the first time, building regional 3D models of measured, extrinsic, and hence intrinsic Q for the North Sea.  You will investigate the interpretative advantages of robust Q-compensation to a suite of structural styles ranging from crustal architecture to shallow compaction related structures.  A successful demonstration of the applicability of these approaches will motivate reprocessing of other seismic archives, thereby improving the understanding of deep basin processes on the European continental shelf.

Figure 2.  PSDM seismic data, without (left) and with (right) the application of Q-compensation, shown as greyscale seismic profiles and wiggle-traces.  Q-compensation greatly improves subsurface resolution (Gamar-Sadat et al., 2016).

Figure 3. Data availability.  Red lines show 2D seismic reflection profiles from TGS’s North Sea database.

Objectives

In this project, you will work with leading scientists in the University of Leeds’ Institute of Applied Geoscience (IAG) and its industrial partners at TGS.  You will use 2D seismic reflection profiles, spanning the North Sea, to characterise seismic Q, correct it for extrinsic effects using well-log data, and then apply Q-compensation algorithms to the seismic archive.  The uplift in resolution will then facilitate a wide range of possible benefits for structural interpretation.  Objectives for the studentship include, but are not limited to:

1.    Derivation of accurate Q estimates from post-stack seismic reflection data, including resolving the contributions of intrinsic and extrinsic Q components by incorporation of well-log results;

2.    Relating the suite of intrinsic Q values to known lithologies and petrophysical properties;

3.    Develop a suite of case studies across the North Sea that quantitatively demonstrates the enhancement of imaging and its interpretative implications.  These studies will include: deep crustal architecture and basin-controlling fault geometry; pre-Jurassic faulting; sub and intra-salt; differential compaction and top seal integrity.

Potential for High Impact Outcomes

Access to such a large archive of seismic reflection data offers a unique opportunity to characterise crustal structure across an extensive basin setting.  The impacts from this research benefit are not limited only to the understanding of North Sea basin structure, but to the evolution of continental rift systems worldwide.  If industry-seismic data prove useful for this purpose here, it is possible that other archives can be used in the same way.  From a geophysical perspective, resolving the influence of intrinsic vs. extrinsic controls on seismic attenuation adds to the suite of quantitative interpretation methods available to the seismic industry.  With its link to fracture development, robust attenuation measurements will have implications for the continuous seismic monitoring of underground repositories of (e.g.) CO2 and nuclear waste.  It is anticipated that positive outcomes from this studentship will stimulate larger applications for research support, e.g. from NERC through its Geosciences (Earth resources and Sedimentary processes) research areas.

CASE Partner

The proposal has been agreed as a “Partnership Project” with the service company TGS, a leading supplier of multi-client seismic data to the hydrocarbon industry.  Besides contributing additional funding to the NERC student stipend, TGS provides access to their seismic reflection data archive from the North Sea, together with financial support for a 3-month internship for the successful student in their Bedford office.  The benefit to TGS is a refined means of measuring the seismic quality factor, including validation of an automated Q-compensation algorithm to improve the resolution of North Sea hydrocarbon targets at depth.

Training

The student will work under the supervision of Dr Roger Clark, Dr Adam Booth and Dr Douglas Paton, within the Institute of Applied Geoscience (IAG) in Leeds’ School of Earth and Environment.  A three-month secondment, distributed throughout the duration of the studentship, will be undertaken at the Bedford office of TGS.  This project can provide high-level specialist training in:

  • quantitative analysis of reflection seismic data and integration of well-log data,

  • use of seismic processing and interpretation software (e.g., Landmark SeisSpace, Schlumberger Petrel)

  • structural geology interpretation and basin evolution.

Co-supervision will involve regular meetings between all partners. The successful candidate will have access to a broad range of MSc-level courses (e.g., in seismic reflection processing and seismic interpretation) through Leeds’ MSc Exploration Geophysics and MSc Structural Geology with Geophysics programmes.

Student Profile

Candidates should have a keen interest in the quantitative analysis of seismic data, and ideally a strong background in geophysics.  Experience with computer programming is essential, using (e.g.) Matlab, Python or equivalent languages.  Familiarity with seismic processing and visualisation software is desirable, as is an understanding of structural geology and basin evolution.

References

England RW and Soper NJ (1997); Lower crustal structure of the East Irish Sea from deep seismic reflection data.  Geological Society of London Special Publications, 1997, v124, 61-72.

Gamar-Sadat F and 5 others (2016); Image quality enhancement using volumetric Q-tomogrpahy and Q-PSDM – Martin Linge Case Study; European Association of Geoscientists and Engineers Annual Conference, Vienna 2016, Th STZ0 10.

Mangriotis M-D and 3 others (2013); Scattering versus intrinsic attenuation in the vadose zone: a VSP experiment. Geophysics, 78(2), B49-B63.

Reine C and 2 others (2012); Robust pre-stack Q determination using surface seismic data – I. Method and synthetic examples. Geophysics, 77(1), R45-R56.

Shapiro SA and Zien H (1993); The O-Doherty-Anstey formula and localization of seismic waves. Geophysics, 58(5), 736-740.

Woods D (2016); A critical analysis of a post-stack batch-Q-estimation algorithm. Unpublished thesis, MSc Exploration Geophysics, University of Leeds.

Related undergraduate subjects:

  • Geophysical science