Seismic attributes in the search for fracture plays

Narhari, Srinivasa Rao; Singh, Sunil Kumar; Al-Ajmi, Neema Hussain; Al-Eidan, Ahmad Jaber

doi:10.1190/1.2792454

Cited by 5 publications

(1 citation statement)

References 2 publications

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“…Neves et al (2004) combined coherence and spectral decomposition attributes with traditional interpretation approaches to improve the detailed interpretive quality and map potential fractured zones in reservoirs. On the other hand, image processing technologies are often used to enhance seismic attributes, such as edge detection (AI-Dossary and Marfurt, 2003), lineament-preserving filtering (AI-Dossary and Marfurt, 2007), the Hough transform (Hassen and Marfurt, 2003), and image enhancement (Narhari et al, 2007), and etc. The 2D histogram equalization algorithm has also been applied to coherence profiles for lithology distribution (Sanguinetti, 2006).…”

Section: Introductionmentioning

confidence: 99%

Coherence cube enhancement based on local histogram specification

2010

Appl. Geophys.

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Coherence analysis is a powerful tool in seismic interpretation for imaging geological discontinuities such as faults and fractures. However, subtle faults or fractures of one stratum are difficult to be distinguished on coherence sections (time slices or profiles) due to interferences from adjacent strata, especially these with strong reflectivity. In this paper, we propose a coherence enhancement method which applies local histogram specification (LHS) techniques to enhance subtle faults or fractures in the coherence cubes. Unlike the traditional histogram specification (HS) algorithm, our method processes 3D coherence data without discretization. This method partitions a coherence cube into many sub-blocks and self-adaptively specifies the target distribution in each block based on the whole distribution of the coherence cube. Furthermore, the neighboring blocks are partially overlapped to reduce the edge effect. Applications to real datasets show that the new method enhances the details of subtle faults and fractures noticeably.

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Section: Introductionmentioning

confidence: 99%

Coherence cube enhancement based on local histogram specification

2010

Appl. Geophys.

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Understanding fractures through seismic data: North Kuwait case study

Narhari

Al‐Kandari

Kidambi

et al. 2009

SEG Technical Program Expanded Abstracts 2009

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Understanding fracture corridors is the primary driver for successful development of fractured carbonate reservoirs. This assumes further significance if the carbonate reservoir is characterized by very low porosity and permeability; producibility of the reservoir is purely dependent on the presence of natural fractures. Distribution and type of natural fractures is a function of palaeo & present day stress, structural elements, regional tectonics and diagenetic history. Direct detection of fractures is below the resolution of conventional seismic data. However, through a combination of seismic derived attributes integrated with well data, it is possible to better understand the distribution of fracture swarms.Kuwait Oil Company (KOC) is currently engaged in an early phase of development of a tight fractured carbonate North Kuwait Jurassic gas play. Considering the limited well control, field development is heavily reliant on seismic data for fracture characterization. This paper presents our current understanding of the relationship between fractures observed in the well data and structures, faults and lineaments interpreted on seismic data. In addition to conventional seismic analysis a suite of seismic attributes including Dip, Coherence, Edge and 3D Volume curvature were used for mapping structures, faults and minor lineaments. Well-wise and field-wise analysis of relationships between seismic derived attribute-pattern and fracture orientation was established. The understanding between these two different sets of data has helped in locating potential zones of sweet spots for placing successful delineation and development wells. These seismic attribute volumes were also used as soft constraint for building the Discrete Fracture Network (DFN) model for populating the fracture network in the reservoir model.

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