Unconventional seismic attributes for fracture characterization

Jaglan, Hardeep; Qayyum, Farrukh; Hélène, Huck

doi:10.3997/1365-2397.33.3.79520

Cited by 40 publications

(22 citation statements)

References 13 publications

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“…Truncated horizons Issaran field is affected by complex structuration (normal faults), which results in seismic velocity differences at structural element locations. Moreover, at their terminations, these structural features yield diffraction noises and seismic wave scattering (Jaglan et al 2015;Bashir et al 2020) and anhydrite cement to spread laterally and vertically within the Issaran field's reservoir layers. As a result, the seismic waves were scattered and dispersed, resulting in a low signal-to-noise ratio and spatial resolution of Issaran seismic data (Sarhan, 2017;Bouchaala et al, 2018;Rao and Wang, 2019).…”

Section: Prevailing Geoseismic Conditionsmentioning

confidence: 99%

“…Sequentially, the methodology started by seismic data conditioning. It is an important step in removing the residual coherent and random noises that remain after seismic data processing (Jaglan et al 2015;Ashraf et al 2020;Attia et al 2020). It is an essential step before beginning the seismic interpretation.…”

Section: Seismic Data Conditioningmentioning

confidence: 99%

“…As illustrated in Fig. 5, the low-and highfrequency noises were eliminated (Helal et al 2015;Jaglan et al 2015), without degrading the main signals of Issaran seismic data.…”

Section: Frequency Filtermentioning

confidence: 99%

“…The seismic dips that will be used in steering generation can be calculated using a variety of methods, including phasebased, amplitude-based, and amplitude-frequency-based methods (Tingdahl and de Rooij 2005;Chopra and Marfurt 2007a). In this study, a phase-gradient algorithm is used for steering generation (Odoh et al 2014;Jaglan et al 2015), from which we can extract information about the azimuth and local dip of reflectors, as well as associated discontinuities of Issaran field.…”

Section: Steering Generationmentioning

confidence: 99%

“…The background steering data is heavily filtered and holds regional information about the regional dip and azimuth of the structure of the studied area (Fig. 6a), while the detailed steering data is smoothly filtered and contains detailed information about the structure and geological features (Jaglan et al 2015) of the studied area (Fig. 6b).…”

Section: Steering Generationmentioning

confidence: 99%

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RETRACTED ARTICLE: Improvement of seismic data quality and recognition of fault discontinuities through seismic data conditioning applications: a case study of Issaran oil field, Gulf of Suez, Egypt

Isaac

Ata

2022

J Petrol Explor Prod Technol

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Obtaining high-quality seismic imaging in shallow heterogeneous carbonate reservoirs with complicated structural regimes, such as the Issaran field, is difficult. Issaran field is a heavy oil shallow heterogeneous fractured carbonate reservoirs located in the Gulf of Suez of Egypt. It has many geological factors that affect image quality and pose numerous challenges. In addition, the seismic data was acquired more than 12 years ago, with narrow azimuth and short offsets. As a result, the fault zones are not sharply defined. Furthermore, the seismic data was processed about 10 years ago. The signal-to-noise ratio is relatively poor due to the random and coherent noises. A robust data conditioning workflow for noise suppression and fault discontinuity sharpening is used to improve the post-stack seismic data quality. In this context, a steering dataset was generated, and a dip-steered median filter (DSMF), a dip-steered diffusion filter, and a fault enhancement filter (FEF) were applied to sharpen the discontinuities. Structural attributes were evaluated, to investigate how the newly applied data conditioning affects the clarity of fault patterns. Furthermore, multiple physical attributes were extracted, including instantaneous phase, instantaneous frequency, and RMS amplitude to better understand the reservoir stratigraphic heterogeneity. The application of DSMF is useful in removing the residual random noises. The FEF-similarity attribute revealed small-scale faults with a 50-foot vertical throw. The physical attributes proved that the Issaran carbonate facies is controlled by structure. Moreover, the RMS amplitude attribute helped in distinguishing between porous and non-porous dolomite facies. As imaging quality has significantly improved, the applied seismic data conditioning workflow is beneficial for the field development in Issaran field. It is also suggested that this data conditioning workflow be applied in other heterogeneous carbonate reservoirs with complex structures around the world.

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Section: Prevailing Geoseismic Conditionsmentioning

confidence: 99%

Section: Seismic Data Conditioningmentioning

confidence: 99%

“…As illustrated in Fig. 5, the low-and highfrequency noises were eliminated (Helal et al 2015;Jaglan et al 2015), without degrading the main signals of Issaran seismic data.…”

Section: Frequency Filtermentioning

confidence: 99%