Source rock types, distribution and their hydrocarbon generative potential within the Paleogene Sokor-1 and LV formations in Termit Basin, Niger

Lai, Hongfei; Li, Meijun; Mao, Fengjun; Liu, Jiguo; Xiao, H.; Tang, Yuan; Shi, Shengbao

doi:10.1177/0144598720915534

Cited by 18 publications

(10 citation statements)

References 24 publications

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“…These results suggest a cleaner and more consolidated reservoir sandstone interval in wells_2 and _3 than in wells_4, _5 and _9. These variations could be attributed to differences in the environment of deposition, burial depths and diagenetic alterations across wells resulting to increased matrix stiffness at reduced porosity and high elastic wave velocities in wells _2 and _3 than the low velocity sands in wells_4, _5 and _9 (Avseth et al 2000(Avseth et al , 2010Chopra and Marfurt 2006;Lai et. al.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

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Rock physics diagnostic of Eocene Sokor-1 reservoir in Termit subbasin, Niger

Hassane

Ehirim

Dagogo

2021

J Petrol Explor Prod Technol

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Eocene Sokor-1 reservoir is intrinsically heterogeneous and characterized by low-contrast low-resistivity log responses in parts of the Termit subbasin. Discriminating lithology and fluid properties using petrophysics alone is complicated and undermines reservoir characterization. Petrophysics and rock physics were integrated through rock physics diagnostics (RPDs) modeling for detailed description of the reservoir microstructure and quality in the subbasin. Petrophysical evaluation shows that Sokor-1 sand_5 interval has good petrophysical properties across wells and prolific in hydrocarbons. RPD analysis revealed that this sand interval could be best described by the constant cement sand model in wells_2, _3, _5 and _9 and friable sand model in well_4. The matrix structure varied mostly from clean and well-sorted unconsolidated sands as well as consolidated and cemented sandstones to deteriorating and poorly sorted shaly sands and shales/mudstones. The rock physics template built based on the constant cement sand model for representative well_2 diagnosed hydrocarbon bearing sands with low Vp/Vs and medium-to-high impedance signatures. Brine shaly sands and shales/mudstones were diagnosed with moderate Vp/Vs and medium-to-high impedance and high Vp/Vs and medium impedance, respectively. These results reveal that hydrocarbon sands and brine shaly sands cannot be distinctively discriminated by the impedance property, since they exhibit similar impedance characteristics. However, hydrocarbon sands, brine shaly sands and shales/mudstones were completely discriminated by characteristic Vp/Vs property. These results demonstrate the robust application of rock physics diagnostic modeling in quantitative reservoir characterization and may be quite useful in undrilled locations in the subbasin and fields with similar geologic settings.

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Section: Discussion Of Resultsmentioning

confidence: 99%

“…These formations are penetrated and dissected by northwest-southeast (NW-SE) synthetic and north-northwest south-southeast (NNW-SSE) antithetic normal faults, respectively (Fig. 3), and northeast-southwest (NE-SW) transpressional anticlines (Lai et. al.…”

Section: Geology Of the Study Areamentioning

confidence: 99%

Rock physics diagnostic of Eocene Sokor-1 reservoir in Termit subbasin, Niger

Hassane

Ehirim

Dagogo

2021

J Petrol Explor Prod Technol

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“…Source rocks can only be evaluated using regional geological and seismic data (Mi et al, 2007;Liu et al, 2007;Cao et al, 2009;Gu et al, 2011), applied sequence stratigraphy (Liu et al, 2007;Huang et al, 2015;Lai et al, 2020), seismofacies and seismic attributes (Cao et al, 2009) in regions without wells. Previous studies showed that middle-deep lacustrine, high quality source rocks were developed in Wenchang Formation of Kaiping sag (Pang et al, 1995;Li et al, 2013Li et al, , 2014.…”

Section: Geological Understandings Of Middle-deep Lacustrinementioning

confidence: 99%

“…If geochemical data were obtained, the relationships between TOC and logging curves, TOC and seismic response could be used for fitting the relationships of source rocks on well and seismic data. Thus, quantitative evaluation and prediction of source rock could be achieved (Herron et al, 1988;Hou et al, 1998;Peters et al, 2006;Keym et al, 2006;Lai et al, 2020). For regions with no well, sedimentary facies characterization can provide constrains for the source rocks.…”

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confidence: 99%

Distribution Prediction of Middle‐deep Lacustrine Source Rocks in Eocene Wenchang Formation in the Kaiping Sag, Pearl Mouth Basin

Xiong¹,

Xie²,

Zhao³

et al. 2021

Acta Geologica Sinica (Eng)

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Oil and gas shows are rich in drilling wells in Kaiping sag, however, large oilfield was still not found in this area. For a long time, it is thought that source rocks were developed in the middle-deep lacustrine facies in the Eocene Wenchang Formation, while there is no source rocks that in middle-deep lacustrine facies have been found in well. Thickness of Wenchang Formation is big and reservoirs with good properties could be found in this formation. Distribution and scale of source rock are significant for further direction of petroleum exploration. Distribution characterization of middle-deep lacustrine facies is the base for source rock research. Based on the sedimentary background, fault activity rate, seismic response features, and seismic attributes were analyzed. No limited classification method and multi-attributes neural network deep learning method were used for predicting of source rock distribution in Wenchang Formation. It is found that during the deposition of lower Wenchang Formation, activity rate of main fault controlling the subsag sedimentation was bigger than 100 m/Ma, which formed development background for middle-deep lacustrine facies. Compared with the seismic response of middle-deep lacustrine source rocks developed in Zhu I depression, those in Kaiping sag are characterized in low frequency and good continuity. Through RGB frequency decomposition, areas with low frequency are main distribution parts for middle-deep lacustrine facies. Dominant frequency, instantaneous frequency, and coherency attributes of seismic could be used in no limited classification method for further identification of middle-deep lacustrine facies. Based on the limitation of geology knowledge, multi-attributes of seismic were analyzed through neural network deep learning method. Distribution of middle-deep lacustrine facies in the fourth member of Wenchang Formation is oriented from west to east and is the largest. Square of the middle-deep lacustrine facies in that member is 154 km 2 and the volume is 50 km 3. Achievements could be bases for hydrocarbon accumulation study and for exploration target optimization in Kaiping sag.

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“…Several authors [7] [8] [9] [10] [11], have adopted different approaches to estimate petrophysical properties and their distribution from well log data in LCLR reservoirs in Termit sub-basin. Similarly, [12] [13] [14] [15] [16], have proposed different techniques for fluid and lithology discrimination in reservoir characterizations.…”

Section: Introductionmentioning

confidence: 99%

Well-Based Quantitative Reservoir Characterization of Eocene Sokor-1 Formation, Termit Basin, Niger

Hassane¹,

Ehirim²,

Dagogo³

2021

IJG

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The Eocene Sokor1 Formation is proven oil reservoir rocks in the Termit sub-basin. These sandstone intervals are deeply buried, highly heterogeneous in character and characterized by Low Contrast Low Resistivity (LCLR) log responses. Petrophysical and quantitative well-based rock physics interpretations were integrated for property estimations, fluid and lithology typing in reservoir characterization. Six (6) reservoir sandstone intervals were identified, delineated and correlated across five (5) wells. The estimated petrophysical properties showed that the Eocene Sokor1 sandstones have averagely good reservoir properties with sand_5 interval exhibiting exceptional reservoir properties. V p /V s vs. AI and μρ vs. λρ elastic cross-plots color coded with reservoir properties (V sh and ϕ), show distinct and well separated data clusters signifying hydrocarbon bearing sandstones, brine sandstones and shales/mudstones in the 3D crossplot planes with varying seismic elastic property values in each well thereby, enhancing reservoir characterization and providing information's about the burial history, reservoir quality and property distribution in the sub-basin. The analysis suggests that, although the reservoir interval has averagely good petrophysical properties in all wells, the seismic elastic crossplots show that these properties are much better distributed in wells 2 and 3 than in wells 4, 5 and 9. Therefore, sand_5 reservoir interval in wells 2 and 3 is likely to be more hydrocarbon bearing and productive than wells 4, 5 and 9 in the sub-basin.

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Source rock types, distribution and their hydrocarbon generative potential within the Paleogene Sokor-1 and LV formations in Termit Basin, Niger

Cited by 18 publications

References 24 publications

Rock physics diagnostic of Eocene Sokor-1 reservoir in Termit subbasin, Niger

Rock physics diagnostic of Eocene Sokor-1 reservoir in Termit subbasin, Niger

Distribution Prediction of Middle‐deep Lacustrine Source Rocks in Eocene Wenchang Formation in the Kaiping Sag, Pearl Mouth Basin

Well-Based Quantitative Reservoir Characterization of Eocene Sokor-1 Formation, Termit Basin, Niger

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