Structural and sedimentary discontinuities control the generation of karst dissolution cavities in a carbonate sequence, Potiguar Basin, Brazil

Araújo, Raphael Ferreira de Souza Bezerra; Bruna, Vincenzo La; Rustichelli, Andrea; Bezerra, Francisco H.R.; Xavier, M. M.; Audra, Philippe; Barbosa, José Antônio; Antonino, Antônio Celso Dantas

doi:10.1016/j.marpetgeo.2020.104753

Cited by 46 publications

(23 citation statements)

References 84 publications

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“…This formation is characterized by the presence of a monotonous and homogeneous succession of carbonate rocks predominantly classified as mudstones, grainstones, and packstones, composed of grains of primary carbonate minerals (calcite) with strong posterior transformation of primary minerals for dolomite [30], [46], [47]. Grainstones are grain-supported rocks and have a relatively small fraction (<1%) of clay-like grain material (<20µm), while packstone is a supported rock by grains, but with a clay fraction ratio >1%, and mudstones are not supported by grains and are predominantly formed by fragments of grain size <20µm [48].…”

Section: Methods Validation a Study Area And Geological Settingsmentioning

confidence: 99%

“…From this data, our proposed workflow is applied and validated generating a 3D stochastic DFN and estimating the volumetric fracture intensity for the model cells. This region is well studied in geological terms [29], [30], however no study regarding outcrop geometry and generation of 3D stochastic was carried. This work is presented as follows: the proposed method, statistics and computations to extract 3D data are presented in Section 2; the interpretation scenario and experimental setting are presented in Section 3; followed by the results and comparisons in Section 4; accompanied by the discussion and finding conclusion.…”

Section: Introductionmentioning

confidence: 99%

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Spherical K-Means and Elbow Method Optimizations With Fisher Statistics for 3D Stochastic DFN From Virtual Outcrop Models

et al. 2022

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Fracture modeling plays a valuable role to understand the fluid flow in carbonate reservoirs. For this, the fracture characterization to generate Discrete Fracture Networks (DFNs) can take advantage of analogue outcrops through Virtual Outcrop Models (VOMs), acquired by Unmanned Aerial Vehicles (UAV) and digital photogrammetry. The stochastic DFN generation is an important step in reservoir modeling as it brings more representative data to the process and has long been studied. However, optimizations concerning automatizing some of the steps necessary to its generation like data clustering are still open to advancements. In this sense, this work aims the fracture data clustering and the definition of the number of clusters when gathering data for the stochastic process, developing an Elbow method for spherical data and a balanced K-means, both based on Fisher statistics. For this, we interpreted fracture planes in a VOM that recreates a carbonate reservoir analogue from the Jandaíra Formation, in the Northeast, Brazil. As result, we show a workflow for immersive fracture interpretation alongside a 3D stochastic DFN model with fracture intensity of 22.57m −1 for cell sizes of 1m 3 . Regarding the clustering balance, our method achieved a lower standard deviation between sets while maintaining the Fisher values greater to obtain fracture sets with lower dispersion. Additionally, the Elbow method implementation proved a beneficial step to the workflow as it reduced the interpretation bias of family clusters. These results alongside the proposed workflow bring a better understanding of the outcrop geometry while offering data scalability for reservoir modeling.

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Section: Methods Validation a Study Area And Geological Settingsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spherical K-Means and Elbow Method Optimizations With Fisher Statistics for 3D Stochastic DFN From Virtual Outcrop Models

et al. 2022

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“…The carbonate karst reservoirs formed by karstification that refers to the comprehensive geological action of water on soluble rocks, including chemical dissolution, mechanical erosion, material migration and re-deposition (Saller et al, 1994;Robert, 1999;Qian et al, 2007). These karst reservoirs have been discovered in many petroliferous basins, such as the Mishrif Formation of Cretaceous in Iraq (Hollis, 2011;Zhao et al, 2019), the Khuff Formation in Oman (Beckert et al, 2016), the Jandaíra Formation of the Late Cretaceous in the Potiguar Basin of northeastern Brazil (Araújo et al, 2021;Bagni et al, 2022). There are many deep karst reservoirs in the Ordovician Formation of the Tarim Basin (Qian et al, 2007), the Cambrian-Ediacaran Formation of the Sichuan Basin (Tan et al, 2015) and the Ordovician Formation in the Ordos Basin in China (Huang et al, 2010).…”

Section: Carbonate Karst Reservoirsmentioning

confidence: 99%

Enrichment Mechanism and Prospects of Deep Oil and Gas

Hao

2022

Acta Geologica Sinica (Eng)

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With the deepening of oil and gas exploration, the importance of depth is increasingly highlighted. The risk of preservation of storage space in deep reservoirs is greater than that in shallow and medium layers. Deep layers mean older strata, more complex structural evolution and more complex hydrocarbon accumulation processes, and even adjustment and transformation of oil and gas reservoirs. This paper systematically investigates the current status and research progress of deep oil and gas exploration around the world and looks forward to the future research focus of deep oil and gas. In the deep, especially the ultra-deep layers, carbonate reservoirs play a more important role than clastic rocks. Karst, fault•karst and dolomite reservoirs are the main types of deep and ultra-deep reservoirs. The common feature of most deep large and medium-sized oil and gas reservoirs is that they formed in the early with shallow depth. Fault activity and evolution of trap highs are the main ways to cause physical adjustment of oil and gas reservoirs. Crude oil cracking and thermochemical sulfate reduction (TSR) are the main chemical modification effects in the reservoir. Large-scale high-quality dolomite reservoirs is the main direction of deep oil and gas exploration. Accurate identification of oil and gas charging, adjustment and reformation processes is the key to understanding deep oil and gas distribution. High-precision detection technology and high-precision dating technology are an important guarantee for deep oil and gas research.

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“…So, to carry out engineering construction in karst areas and to improve the stability of engineering structures and later safety maintenance, it is necessary to understand the characteristics of rock dissolution law in soluble rock areas, predict its development trend, and provide assurance for early identification and safety evaluation of karst geological disasters. Europe, the United States, and other countries and regions have carried out large-scale karst landforms [ 1 , 2 ], hydrogeology [ 3 , 4 ], karst environment [ 5 , 6 ], and other aspects to further develop karst research.…”

Section: Introductionmentioning

confidence: 99%

Development and Application of Carbonate Dissolution Test Equipment under Thermal–Hydraulic–Chemical Coupling Condition

et al. 2022

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The latest continuous flow micro reaction technology was adopted to independently develop carbonate rock dissolution test equipment. Carbonate rock dissolution tests were conducted under different temperatures, flow rates, and dynamic water pressure conditions to study the dissolution process of carbonate rocks under the coupling of heat-water-chemistry. The dissolution effect and development law of carbonate rocks were explored by quantitatively studying carbonate rock dissolution rate and chemical composition of karst water. The results showed that the self-designed dissolution test equipment has obvious advantages. After dissolution, carbonate rock specimens were damaged to varying degrees. The dissolution rate was proportional to water velocity and hydrodynamic pressure, with the velocity effect being greater than the hydrodynamic pressure effect. The pH value, conductivity, and Ca2+ ion content of the reaction solution gradually increased after dissolution. The development and application of the equipment have proved that, at low dynamic water pressures (2 MPa), the water flow velocity effect on the dissolution velocity was 1.5 times that when the dynamic water pressure was high (6 MPa); at a low water flow velocity of 15 mL/min, the dynamic water pressure effect on the dissolution velocity was three times that when the water flow velocity was high (75 mL/min). The development process is gradually becoming strong and stable. Its research has important theoretical significance and engineering application value to provide technical means and guarantee for the early identification, karst development, and safety evaluation of karst geological disasters.

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Structural and sedimentary discontinuities control the generation of karst dissolution cavities in a carbonate sequence, Potiguar Basin, Brazil

Cited by 46 publications

References 84 publications

Spherical K-Means and Elbow Method Optimizations With Fisher Statistics for 3D Stochastic DFN From Virtual Outcrop Models

Spherical K-Means and Elbow Method Optimizations With Fisher Statistics for 3D Stochastic DFN From Virtual Outcrop Models

Enrichment Mechanism and Prospects of Deep Oil and Gas

Development and Application of Carbonate Dissolution Test Equipment under Thermal–Hydraulic–Chemical Coupling Condition

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