Fault System Analysis Using a New Interpretation Paradigm

Skov, T.; Pedersen, Stein Inge; Valen, T.S.; Fayemendy, P.; Grønlie, A.; Hansen, Jan Ove; Hetlelid, A.; Iversen, Thomas Fridolin; Randen, T.; Sønneland, L.

doi:10.3997/2214-4609-pdb.6.b31

Cited by 14 publications

(4 citation statements)

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“…In the ant attribute algorithm, large numbers of electronic ants are distributed in the seismic volume allowing them to move along faults and emitting pheromones. Surfaces that are strongly marked with pheromones are likely to fault [28][29][30]. Ant track cube has been constructed according to the workflow (Figure -11).…”

Section: Ant -Track Attributementioning

confidence: 99%

Using Chaos and Ant Track Attributes to Recognize The Faulting Systems and Subtle Faults of a Jurassic - Cretaceous Sedimentary Packages in Merjan_West Kifl Oil Fields - Central Iraq

Fadhil¹,

Al-Rahim

2019

eijs

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Study of three dimensional seismic data of Merjan area-central Iraq has shown that the Jurassic â€“ Cretaceous succession is affected by faulting system. Seven major normal faults were identified and mapped. Synthetic traces have been calculated by using sonic and density log data of the well Me-1.Two exploration wells were drilled in the area Me-1 and Wkf-1 wells, the distance between them is 15.82 km. Discussion about the effect of this system on the sedimentary package has been presented. The tight faults that couldnâ€™t be distinguished it on seismic sections were determined using seismic attributes. They have different strike and limited in their vertical and horizontal extension. They are system facilitates the movement or migration of the fluid across the stratigraphic column in the study area. Faulting framework can be divided into two groups: the first affects the Jurassic and lower Cretaceous rocks and the second effect the upper Cretaceous and lower Tertiary rocks. The first group is associated with the post rift thermal sag, passive margin progradation and gravitational collapse (lower Jurassic â€“ upper Cretaceous (Turonian) 022 â€“ 93 Ma); approximately Sargelue â€“ NahrUmr depositional time. The second group is few and is associated with the rifting creating the Euphrates graben (Late Turonian â€“ Maastrichtian 90 â€“ 70 Ma) approximately Tanuma shale / Sadi â€“ Shiranish) depositional time.

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Section: Ant -Track Attributementioning

confidence: 99%

Using Chaos and Ant Track Attributes to Recognize The Faulting Systems and Subtle Faults of a Jurassic - Cretaceous Sedimentary Packages in Merjan_West Kifl Oil Fields - Central Iraq

Fadhil¹,

Al-Rahim

2019

eijs

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“…By populating a preprocessed 3D seismic volume with computer agents coded to follow discontinuities,the ant tracking algorithm,as in Eq.1 and Eq.2,is used to identify, sharpen and track fratures [4] .…”

Section: Ant Colony Optimization Algorithms(aco)mentioning

confidence: 99%

Automatic Fracture Identification Using Ant Tracking in Tahe Oilfield

Kang

Yuan

2014

AMR

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There were many ways for the identification of 3D seismic data of fracture system,and the traditional manual fracture identification was time consuming.The automatic ant tracking technique for fractures based on ant colony optimization (ACO) is a new method developed in recent years.It displays clearly the distribution of fracture systems and faults.Compared to manual interpretation which only identifys a small amount of very obvious fractures and faults,the new method is more objective,and more clear, accurate and intuitive.This paper proposed the research idea of taking Tahe oilfield 4th block as an example,to identify fractures and to set up the fracture model.The model can display 3D structure shape of the reservoir and have achieved good results.

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“…Mapping the amplitude heterogeneity reveals structural edges in the elastic properties of the subsurface rocks. The methods for extraction of faults using the concept of heterogeneity delineation were described by Pedersen et al (2002Pedersen et al ( , 2003 and Skov et al (2003). Lineaments are correlated with the lines of elastic impedance contrast, which often occur along normal faults.…”

Section: Measurements and Techniquesmentioning

confidence: 99%

Multi‐measurement integration for near‐surface geological characterization

Laake¹,

Strobbia²

2012

Near Surface Geophysics

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Geological characterization of the near‐surface is challenging because often shallow layers are unconsolidated and their properties have rapid and significant variations in vertical and lateral directions. This creates challenges for a majority of geophysical methods, which have limitations in the presence of a complex distribution of physical properties and that give optimal results over limited depth intervals, which are different for the different methods. The shallow near‐surface depth region is often problematic for standard seismic exploration methods. As a result, geological characterization through individual measurements is often compromised. The solution proposed here is the integration of multiple measurements of surface and deep subsurface properties, with the goal of generating a geologically meaningful lithostructural model of the near‐surface. The underlying idea is based on the observation that deep subsurface structural features often leave an impression on the surface. This provides an opportunity for structural mapping at the surface and below the bottom of the near‐surface zone to guide the processing and interpretation of data from the near‐surface. We show how the integration of multiple data sets from the measurement of different physical properties can be used to generate and enhance specific near‐surface products such as drilling risk maps or P‐wave velocity models for static corrections or for velocity modelling. The analysis proves that integration of multiple data sets can provide a solution when individual measurements, such as refraction traveltimes, do not provide sufficient information to characterize the lithostructure of the near‐surface. Satellite surface imagery and deep seismic data can provide the structural framework for the processing and interpretation of shallow seismic data. Simultaneous joint inversion of shallow P‐ and S‐wave data reveals the vertical and lateral velocity structures in the near‐surface, which are usually concealed when only refraction data are used. Finally, the correlation of multiple data sets in a correct spatial reference provides a quality control for the data set and allows for the lithostructural interpretation of data in the near‐surface.

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Fault System Analysis Using a New Interpretation Paradigm

Cited by 14 publications

References 0 publications

Using Chaos and Ant Track Attributes to Recognize The Faulting Systems and Subtle Faults of a Jurassic - Cretaceous Sedimentary Packages in Merjan_West Kifl Oil Fields - Central Iraq

Using Chaos and Ant Track Attributes to Recognize The Faulting Systems and Subtle Faults of a Jurassic - Cretaceous Sedimentary Packages in Merjan_West Kifl Oil Fields - Central Iraq

Automatic Fracture Identification Using Ant Tracking in Tahe Oilfield

Multi‐measurement integration for near‐surface geological characterization

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