Characteristics and influence factors of basement buried-hill reservoir in Bongor Basin, Chad

Yu, Zhisheng; Du, Yebo; Xiao, Kunye; Wang, Jingchun; Xiao, Gaojie; Zhang, Guilin; Liang, Qiao-feng; Wang, Yuhua

doi:10.18654/1000-0569/2019.04.20

Cited by 16 publications

(3 citation statements)

References 16 publications

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“…Currently, some studies have reported on the classification schemes for granite weathering crust (Chen et al 2016;Huang et al 2016;Xu et al 2016;Dou et al 2015Dou et al , 2018Wang et al 2018;Zhu et al 2020), and the characteristics of granite reservoirs have also been clarified, which mainly include the physical characteristics of granite, genetic mechanisms, fracture development characteristics, and reservoir reconstructions (Zhou et al 2005;Yang et al 2013;Li 2016;Xia 2016;Zhao et al 2019;Ye et al 2020Ye et al , 2021. In addition, the main reservoir spaces of weathering crust reservoirs comprise dissolution pores and fractures and varying properties of different structural layers (Song et al 2011;Xu et al 2016;Huang et al 2020;Bai et al 2021;Du et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Study on seismic characterization and distribution characteristics of effective reservoirs of granite weathering crust in Dongying Sag, Bohai Bay Basin

Zhu,

Liu,

Liu

et al. 2024

J Petrol Explor Prod Technol

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To solve the problem of low resolution of seismic data from granite weathering crust and difficulty in predicting effective reservoir distribution. Based on the research idea of combining geology and seismology, seismic facies characteristics and effective reservoir distribution of granite weathering crust are studied by means of frequency division reconstruction processing, seismic facies analysis and sensitive attributes interpretation. This method consists of the following four main processes: (1) Using improved Morlet wavelet function for frequency division and reconstruction processing of seismic data; (2) From the perspective of geological evolution, analyzing the geological origin of seismic facies; (3) Based on the results of well- seismic combination, clarifying the types of effective reservoirs and predicting their distribution; (4) Comprehensive research indicating favorable reservoirs distribution. The results indicate that (1) a considerably improved resolution of seismic data processed by frequency division reconstruction is obtained based on the improved Morlet wavelet function. Thus, granite reservoirs then have clearer internal reflection characteristics. (2) Affected by differences in weathering, the seismic facies in granite weathering crusts can be classified as follows: Strong-amplitude facies with amplitudes of 23,700 − 32,800, corresponding to eluvium, represents the late stage of weathering crust evolution with high-intensity weathering. Medium-amplitude facies with amplitudes of 5,250 − 24,000, corresponding to dissolution layer, represents a middle stage of weathering crust evolution with moderate weathering. And weak-amplitude-blank facies with amplitudes of 0–5,330, corresponding to disintegration layer, represents an early stage of weathering crust evolution with weak weathering. (3) Effective reservoirs can be classified according to well-seismic calibrations and combined with reservoir spaces, porosities and permeabilities, and the logging and oil-bearing characteristics of the reservoirs. Type I effective reservoir comprises medium-amplitude facies, with favorable reservoir conditions and high-yield oil-bearing properties; this type is distributed in the western slopes, with an elevation of 1,300-2,500 m. Type II effective reservoir comprises strong-amplitude facies, with poor oil-bearing properties; this type is mainly distributed in the southeast and north slopes of the study area, with a relatively limited range, and the elevation is mostly below 1,500 m. Type III effective reservoir comprises weak-amplitude-blank facies, with poor reservoir conditions and poor oil-bearing properties; this type is widely distributed at various elevations. (4) The areas where medium-amplitude facies have developed are the most favorable reservoir exploration zones for granite in Dongying Sag, Bohai Bay Basin.

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Section: Introductionmentioning

confidence: 99%

Study on seismic characterization and distribution characteristics of effective reservoirs of granite weathering crust in Dongying Sag, Bohai Bay Basin

Zhu,

Liu,

Liu

et al. 2024

J Petrol Explor Prod Technol

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“…The development of reservoirs is closely related to lithology and mineral composition, and intrusive rocks make better reservoirs than metamorphic rocks [13,14]. Felsic mineral content is positively correlated with porosity, and dark mineral content is negatively correlated with the petrophysical properties of reservoirs [15][16][17][18]. This directly affects the formation of fractures and indirectly affects the formation of dissolution pores [19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Integrated Identification of Lithology Using Seismic and Magnetic Anomaly Data for Granite and Gneiss Basement: A Case Study of the LiShui Depression in the East China Sea Basin

Zhang

Tang

et al. 2023

Minerals

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Granite and gneiss buried hill reservoirs are controlled by their lithology and dark mineral content. Therefore, lithological identification and dark mineral content analysis are important research tools in the early stage of buried hill exploration. In this paper, the relationships between the seismic facies and lithology, magnetic susceptibility, and magnetic anomalies of granite and gneiss are analyzed based on the lithological characteristics of the LiShui depression (LS depression) in the East China Sea Basin (ECSB). The waveform classification method is used to identify granite and gneiss, and the waveform classification results reveal that areas with continuous distribution of a single seismic trace model or two seismic trace models represent good continuity, and can be interpreted as gneiss. Areas with a mixed distribution of multiple seismic trace models represent chaotic and poor continuity, which can be interpreted as granite. The mixed linear zone with multi-seismic trace models is a fault zone, and the rock is cataclasite. In addition, reduction to the pole (RTP) and downward continuation technique for magnetic data processing were used to determine the dark mineral content. Overall, the granite and gneiss can be divided into three types based on magnetic anomaly data: high, moderate, and low magnetic anomaly areas. The areas in which granite with moderate and low magnetic anomalies is distributed are the favorable exploration target areas. The above method provides a technical means of lithological identification in the early stage of buried hill exploration.

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“…After that, large buried hill oil and gas reservoirs were found around the world (Dake & Bridge, 1932). For example, the Bach Ho oilfield in Vietnam (Cuong et al, 2009), granite reservoirs in the Bongor Basin, Chad (Dou et al, 2015, 2018), the Kudu gas field in Namibia (Zou et al, 2008), the Jawa Basin Jatib Arang oil and gas field in Indonesia (Petford & McCaffrey, 2003), the Xinglongtai buried hill in Liaohe oilfield (Xie et al, 2006), the Dongping gas field in Qaidam Basin ( Guo, Ma, et al, 2017), The Kelameili gas field in Junggar Basin (Kuang et al, 2010), the Xushen gas field in Songliao Basin (Xu et al, 2006) are all large buried‐hill oil and gas reservoirs in the world. Based on the successful exploration experience of these oil and gas fields, the Bohai oilfield has also made significant breakthroughs in buried hill exploration (Hu et al, 2017; Tong et al, 2012; Ye et al, 2020; Zhao et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Formation mechanism and evolution model of buried hill reservoir in BZ19‐6 structural belt, Bozhong Sag, Bohai Bay, East China

Shi,

Xie,

et al. 2023

Geological Journal

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The BZ19‐6 structural belt is the largest buried hill oil‐gas‐bearing area recently discovered in Bohai Bay Basin. The formation and evolution of the buried hill reservoirs are complex. Presently, the development law and controlling factors of this reservoir is unclear. Based on 3D seismic, drilling data, thin section, and regional tectonic background, we explored the controlling factors and development law of the high‐quality buried hill reservoir. The results show that the buried hill reservoir can be vertically divided into a weathered glutenite zone, weathered fracture zone, internal fracture zone, and tight zone. The development of reservoir is mainly controlled by lithotypes, tectonic movement, and weathering. The rocks in the study area with low compressive strength, provided the material basis for the formation of fractures. The strongly reformed multi‐stage tectonic movements provides the external dynamics for the formation of fractures. Weathering further improved the physical properties of the reservoir. The buried hill reservoir is mainly distributed in the weathered fracture zone and internal fracture zone. Currently, natural gas mainly found in nearly E‐W‐trending and N‐S‐trending fractures. The nearly E‐W‐trending fractures are developed in the thrust nappe structure formed by N‐S‐trending extrusion in the Indosinian. The hinge zone of the structure is the main development area of fractures. The nearly N‐S‐trending fractures are associated with strike‐slip faults formed by sinistral strike‐slip stress in the Yanshanian. Under the background of NNE–SSW direction extensional stress during the Himalayan, early fractures were reactivated, opened and expanded, forming the reservoir space for later natural gas charging.

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Characteristics and influence factors of basement buried-hill reservoir in Bongor Basin, Chad

Cited by 16 publications

References 16 publications

Study on seismic characterization and distribution characteristics of effective reservoirs of granite weathering crust in Dongying Sag, Bohai Bay Basin

Study on seismic characterization and distribution characteristics of effective reservoirs of granite weathering crust in Dongying Sag, Bohai Bay Basin

Integrated Identification of Lithology Using Seismic and Magnetic Anomaly Data for Granite and Gneiss Basement: A Case Study of the LiShui Depression in the East China Sea Basin

Formation mechanism and evolution model of buried hill reservoir in BZ19‐6 structural belt, Bozhong Sag, Bohai Bay, East China

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