High-resolution sedimentology and sequence stratigraphy of the Oxfordian-Kimmeridgian, Hanifa, Jubaila and Arab outcrops along Jabal Tuwaiq, Central Saudi Arabia

Al-Mojel, Abdullah; Razin, Philippe; Dera, Guillaume

doi:10.1016/j.jafrearsci.2020.103803

Cited by 42 publications

(62 citation statements)

References 61 publications

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“…The platform outcrops were studied from two regions (Fig. 1a) -Mojel et al, 2020). The platform outcrops in Central Arabia were not described previously for fractures, except from one segment in the CAG (Hancock et al, 1984;Abdlmutalib and Abdullatif, 2017).…”

Section: Methodsmentioning

confidence: 99%

“…1b). The platform is interbedded dolomite and limestone with a wide range of lithofacies, from grain-to mud-dominated; porosity, from 5 to 30%; and bed thicknesses, from 0.1 to 3.5m (e.g., Al-Mojel et al, 2020;Al-Fahmi, 2018). The varying mechanical properties are primarily functions of porosity, and they do not change significantly with the dynamic conditions in areas of oil production and water injection (e.g., Ameen et al, 2009).…”

Section: Late Kimmeridgian Platformmentioning

confidence: 99%

“…Variations in thicknesses and lithofacies in the shelf sequences in Central Arabia were attributed to eustasy and passive tectonics (e.g., Powers et al, 1966;Al-Mojel et al, 2020). The Paleozoic strata were uplifted by reactivation of faults in the underlying basement during the Devonian to early Triassic Hercynian Orogeny (e.g., Powers et al, 1966).…”

Section: Interior Homoclinementioning

confidence: 99%

“…It is also the richest in petroleum, which is prolifically produced from several supergiant fields of anticlinal structures in Eastern Arabia (e.g., Al-Husseini, 1997). Outcrops and subsurface of the platform have been studied over the past seven decades for lithostratigraphy and petrophysics (e.g., Steineke et al, 1958;Powers et al, 1966;Al-Husseini, 1997;Al-Awwad and Collins, 2013;Al-Mojel et al, 2020) and references therein. Research on the platform fractures, veins, and faults is relatively sparse and only fairly recent.…”

Section: Introductionmentioning

confidence: 99%

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New scaling of fractures in a giant carbonate platform from outcrops and subsurface

Al-Fahmi

Hooker

Al-Mojel

et al. 2020

Journal of Structural Geology

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We scale properties of fractures in the Late Kimmeridgian carbonate platform of the Arabian Shelf from outcrop and subsurface strata. The platform is flat-lying undeformed except from low-relief anticlines and domes, at which the strata hosts the world's most prolific petroleum reserves. The strata exhibit stylolites and veins, besides the dominant fractures. The fractures are opening-mode, steep, and forming major sets of NW-SE and NE-SW orientations. Faults are uncommon. Fracture abundance varies significantly across the platform, but it is constrained spatially by inherent variation in mechanical stratigraphy and temporally by anticlinal growth and isotope geochemistry. In early burial stages, the platform strata were slightly deformed by bed-parallel stylolites and mutually crosscutting veins. The strata fracturing increased by the anticlinal growth in the Late Cretaceous. Fracture spacing is an average of 2m in the horizontal-bedded outcrops in Central Arabia and 0.30m in the equivalent subsurface in a dome in Eastern Arabia. The dome is an end member in the deformation spectrum of the platform interior, with up to c. 5° structural dip and 2% dilational strain expressed in the doming and a few major faults. This finding indicates that carbonate platforms can reach fracture oversaturation under such a subtle tectonic extension.

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Section: Methodsmentioning

confidence: 99%

Section: Late Kimmeridgian Platformmentioning

confidence: 99%

Section: Interior Homoclinementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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New scaling of fractures in a giant carbonate platform from outcrops and subsurface

Al-Fahmi

Hooker

Al-Mojel

et al. 2020

Journal of Structural Geology

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“…We test this methodology on the laterally heterogeneous Late Jurassic carbonate rock formations from two different outcrop sites (Figure 1A). Since the depositional facies of these formations are known to be laterally heterogenous (Al-Mojel, Razin, and Dera 2020;Jacquemyn et al 2018), these two outcrops provide a unique opportunity to investigate the applicability of seismic multi-attribute analysis for a near-surface UCS prediction.…”

Section: Introductionmentioning

confidence: 99%

Multiattribute probabilistic neural network for near-surface field engineering application

et al. 2021

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Unconfined compressive strength (UCS) is an important rock parameter required in the engineering design of structures built on top or within the interior of rock formations. In a site investigation project, UCS is typically obtained discretely (through point-to-point measurement) and interpolated. This method is less than optimal to resolve meter-scale UCS variations of heterogenous rock such as carbonate formations in which property changes occur within data spacing. We investigate the geotechnical application of multiattribute analysis based on near-surface reflection seismic data to probe rock formations for their strength attributes at meter-scale variability. Two Late Jurassic outcrops located in central Saudi Arabia serve as testing sites: the Hanifa Formation in Wadi Birk and the Jubaila Formation in Wadi Laban. The study uses core and 2D seismic profiles acquired in both sites, from which we constrain UCS, acoustic velocity, density, and gamma-ray values. A positive linear correlation between UCS and acoustic impedance along the core indicates that seismic attributes can be utilized as a method to laterally extrapolate the UCS away from the core location. Seismic colored inversion serves as input for neural network multiattribute analysis and is validated with a blind test. Results from data at both outcrop sites indicate a high degree of consistency with an absolute UCS error of approximately 5%. We also demonstrate the applicability of predicted UCS profiles to interpret mechanical stratigraphy and map lateral UCS heterogeneities. These findings provide a less expensive alternative to constrain UCS from limited core data on a field-scale site engineering project.

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Pore to Core Scale Characterization of Hydraulic Flow Units Using Petrophysical and Digital Rock Analyses

Chandra,

Tallec,

Finkbeiner

et al. 2023

Energy Tech

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This article illustrates an integrated method for characterizing hydraulic flow units in subsurface reservoirs using multiscale images and petrophysical data analysis from well cores. This method is applied to 35 meters of cores drilled from a Late Jurassic Upper Jubayla Formation outcrop in Saudi Arabia, which is analogous to the lower section of the Arab‐D reservoir. Scanning electron microscope (SEM) imagery, thin‐section petrography, and X‐ray computed tomography (CT) images of whole cores and core plugs are used to visualize and characterize these carbonate rocks across multiple length scales. Core plug porosity and permeability data are used for petrophysical characterization and deriving hydraulic flow units (HFU). The multimodal pore types associated with the HFUs and their connectivity using thin section and SEM image analysis, combined with mercury injection porosimetry are used. Whole‐core CT textures and heterogeneity logs are correlated with HFU and digital image analysis of core plugs. Whole‐core CT data prove to be a highly valuable tool for bridging the scale gap between well data and reservoir models. This methodology can be applied to datasets from a large number of wells, especially when combined with machine learning tools, allowing improved characterization of complex carbonate reservoirs.

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High-resolution sedimentology and sequence stratigraphy of the Oxfordian-Kimmeridgian, Hanifa, Jubaila and Arab outcrops along Jabal Tuwaiq, Central Saudi Arabia

Cited by 42 publications

References 61 publications

New scaling of fractures in a giant carbonate platform from outcrops and subsurface

New scaling of fractures in a giant carbonate platform from outcrops and subsurface

Multiattribute probabilistic neural network for near-surface field engineering application

Pore to Core Scale Characterization of Hydraulic Flow Units Using Petrophysical and Digital Rock Analyses

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