Porosity estimation using a combination of Wyllie–Clemenceau equations in clean sand formation from acoustic logs

Kamel, Manal; Mabrouk, Walid M.; Bayoumi, A.I.

doi:10.1016/s0920-4105(01)00169-3

Cited by 15 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The thickness of present‐day stratigraphic units differs from their original thicknesses due to the reduction of the primary porosity (Schneider et al., 1996). Therefore, we constructed separate porosity‐depth curves in each well based on density, neutron, and sonic logs (Kamel et al., 2002; Raiga‐Clemenceau et al., 1986; Wyllie et al., 1956). Where porosity logs were missing, the curves were generated empirically by adopting the approach of Steckler and Watts (1978) and constrained by data from nearby wells.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Subsidence and Uplift History of the UAE and the Western Flank of the UAE‐Oman Mountain Range

Jabir,

Ali,

Ismaiel

et al. 2023

Tectonics

View full text Add to dashboard Cite

The western flank of the UAE‐Oman mountain range offers a unique geodynamic setting to study the development of a cratonic rift into a mature passive margin and its subsequent flexure under orogenic load. However, the geodynamic processes driving this evolution are not fully understood. In this study, seismic and biostratigraphic data from 283 exploration wells were utilized to assess the regional subsidence and uplift history of the United Arab Emirates (UAE) and neighboring areas of the western flank of the UAE‐Oman mountain range. Three major sequences have been identified: pre‐Permian, Permian‐Turonian rifted margin, and Coniacian‐Pleistocene active margin. Backstripping of biostratigraphic data reveals Early Permian (ca. 272 Ma) and Late Jurassic (ca. 160) rift phases, that have been linked to Gondwana's early and final fragmentation. A NE‐SW‐oriented basin in central UAE suggests a Jurassic intracratonic rift that has been influenced by pre‐existing structures. Compressional phases were identified during the Late Cretaceous and in the Oligocene‐Miocene, Compressional phases were identified during the Late Cretaceous and in the Oligocene‐Miocene, coinciding with the emplacement of the Semail ophiolite and the Arabian‐Eurasian plates collision, respectively. These events caused additional subsidence and flank uplift, forming the Aruma foreland basin in the east and the Pabdeh foreland basin in the eastern and northern UAE. Crustal thickness following the rift episodes ranges from 30 to 36 km, considering a sedimentary cover thickness of 11‐14 km. These estimates are in accord with Moho depths derived from teleseismic receiver functions and gravity inversion. These findings can be used to better understand Gondwana fragmentation and the opening and closing of the Neo‐Tethys Ocean.

show abstract

Section: Methodsmentioning

confidence: 99%

“…The thickness of present-day stratigraphic units differs from their original thicknesses due to the reduction of the primary porosity (Schneider et al, 1996). Therefore, we constructed separate porosity-depth curves in each well based on density, neutron, and sonic logs (Kamel et al, 2002;Raiga-Clemenceau et al, 1986;Wyllie et al, 1956).…”

Section: Backstrippingmentioning

confidence: 99%

Subsidence and Uplift History of the UAE and the Western Flank of the UAE‐Oman Mountain Range

Jabir,

Ali,

Ismaiel

et al. 2023

Tectonics

View full text Add to dashboard Cite

show abstract

“…where x is an exponent specific to the matrix lithology. Kamel et al 5 ) proposed x = 55.196 × 8843 0 tma .…”

Section: Sedimentary Rocksmentioning

confidence: 99%

“…Δ  based on the relationship between the matrix exponent (x) and the matrix transit time (Δtma). In addition, the following equation 5 ) was established by multiplying the time average of Eq. ( 1) and the Raiga-Clemenceau Eq.…”

Section: Sedimentary Rocksmentioning

confidence: 99%

Estimation of Porosity for Sedimentary Rocks and Volcanic Rocks from Sonic Log Data in the Futagawa Fault Drilling

Shibutani,

Lin,

Sano

et al. 2024

Mater. Trans.

View full text Add to dashboard Cite

show abstract

“…As expected, SPyCRID generated a total of 32 data sets with non-unique φ calculated values upon its final iteration. To eliminate more erroneous data sets, data constraints were devised based on data sets having φ calculated values that deviate by less than 5% from the average φ measured value (Table 1), such as also done by Kamel, Mabrouk and Bayoumi (2002) and Lundegard (1992). Information on SPyCRID outputs and their respective φ calculated errors is tabulated in Table 2.…”

Section: E V E L O P M E N T O F S P Y C R I D F Ro M T H E M O D E Lmentioning

confidence: 99%

An unconventional method for calculating porosity of marine clay deposits using the 2D resistivity method

Rosli

Saad

Rahman

et al. 2020

Near Surface Geophysics

View full text Add to dashboard Cite

Various methods were earlier designed to calculate porosity of a formation, but many of them are reliant on physical soil sampling and/or laboratory measurements. The present work examines a recently proposed method, which we call here as Sample-free Porosity Calculation from Resistivity Imaging Data (SPyCRID), to calculate porosity of unconsolidated soils. By conjoining Archie's and Waxman-Smits' equations, SPy-CRID can achieve high accuracy in porosity calculation, while requiring no physical soil-sampling data. Two-dimensional resistivity data acquired at Segantang Garam were modelled to calibrate SPyCRID's workflow and to devise data constraints for marine clay and brackish pore-fluid conditions. Measured porosities from soil samples were used only for calibration and validation purposes. With data transformation added into the workflow, the performance of SPyCRID was improved as it was possible to achieve more precise value for the calculated porosity (error ≤3.1%). The final step to establish SPyCRID's competency was implemented through testing SPy-CRID at the Nibong Tebal test site that has similar geological conditions to the model. Results from this test site showed nominal errors (≤3.9%) in the calculated porosity. SPyCRID could successfully calculate the porosity of the unconsolidated, marine clayey soils with a confidence limit exceeding 96%, while requiring no physical sampling data.

show abstract

Porosity estimation using a combination of Wyllie–Clemenceau equations in clean sand formation from acoustic logs

Cited by 15 publications

References 6 publications

Subsidence and Uplift History of the UAE and the Western Flank of the UAE‐Oman Mountain Range

Subsidence and Uplift History of the UAE and the Western Flank of the UAE‐Oman Mountain Range

Estimation of Porosity for Sedimentary Rocks and Volcanic Rocks from Sonic Log Data in the Futagawa Fault Drilling

An unconventional method for calculating porosity of marine clay deposits using the 2D resistivity method

Contact Info

Product

Resources

About