Fluid storage and migration properties of sheared Neptunian dykes

Parrino, Nicolò; Agosta, Fabrizio; Stefano, Pietro Di; Napoli, Giuseppe; Pepe, Fabrizio; Renda, Pietro

doi:10.1016/j.marpetgeo.2019.01.008

Cited by 12 publications

(2 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Works that have generated 3D stochastic DFN models from strike/dip data relied on visual interpretation of fracture sets in diagrams and statistics generated by 2D software like the FracPaQ [21], [22] and FRACMAN [23] to identify the best quantity of sets. With some works [24], [25] reducing the quantity of sets arbitrarily applying metrics to identify and agglutinate co-planar sets, also using the Fisher concentration to highlight the possible number of clusters in the stereonet.…”

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

View full text Add to dashboard Cite

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.

show abstract

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

View full text Add to dashboard Cite

show abstract

“…They typically occur on highrelief carbonate systems and often form prior to significant burial. Neptunian dikes are frequently found to be sheared by contemporary or later intersecting fault planes and fracture corridors (Parino et al, 2019).…”

Section: Introductionmentioning

confidence: 99%