CO2 flow through a fractured rock volume: Insights from field data, 3D fractures representation and fluid flow modeling

Bigi, Sabina; Battaglia, Maurizio; Alemanni, A.; Lombardi, S.; Campana, A.; Борисова, Е. А.; Loizzo, Matteo

doi:10.1016/j.ijggc.2013.07.011

Cited by 27 publications

(14 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fracture orientations are important to predict the leakage of geofluid from reservoirs (e.g., Bigi et al ) and to estimate the stability of open pit and tunnel walls (Priest ; Peel et al ). The orientations of dilational fractures such as dikes and mineral veins are clues to paleostresses (Stevens ; Anderson ; McHone ; Delaney et al ; Baer et al ; Jolly & Sanderson ; Yamaji et al ; Sato et al ; Kanai et al ).…”

Section: Introductionmentioning

confidence: 99%

Genetic algorithm for fitting a mixed Bingham distribution to 3D orientations: a tool for the statistical and paleostress analyses of fracture orientations

Yamaji

2016

Island Arc

View full text Add to dashboard Cite

The clustering of fracture orientations is important for tectonic studies and for geotechnical engineering. In this study, a real-coded genetic algorithm was adopted to fitting a mixed Bingham distribution to orientation data by maximizing the log-likelihood function of the distribution. The maximization is a difficult problem, because the function has multimodality and singularity. It was found that the algorithm was effective for this problem. Given the orientations of dilational fractures, the present method determines not only the stress axes and stress ratio of each of the fracture groups but also the maximum non-dimensionalized fluid pressure at the time of their formation. In addition, the software calculates the 95 % error ellipses of the concentration axes. The present method found that the orientations of ore veins of the Akenobe Mine, SW Japan, should be partitioned into three clusters. It is shown that two of the groups had distinctive Zn and Sn contents, and that the ore fluids had overpressures only slightly greater than the minimum principal stress at the time of the deposition of Zn-and Sn-rich veins.

show abstract

Section: Introductionmentioning

confidence: 99%

Genetic algorithm for fitting a mixed Bingham distribution to 3D orientations: a tool for the statistical and paleostress analyses of fracture orientations

Yamaji

2016

Island Arc

View full text Add to dashboard Cite

show abstract

“…The method presented in this paper, namely, the development of different schemes for the associated radon and CO 2 discharges and the implementation of quantitative analytical models of radon transport, by contrast with detailed numerical modeling focusing on one set of hypotheses only [e.g., Bigi et al, 2013] and with simple first-order geochemical models based on radon concentration only [e.g., Parks et al, 2013], appears extremely useful to study hydrothermal systems. In addition, the use of radon, considered so far at best as a secondary issue, limited to studies dealing with health hazard, emerges now as particularly relevant, due essentially to the fact that radon half-life is of the order of critical transit times in the crust for environmental and geodynamical concerns.…”

Section: Resultsmentioning

confidence: 99%

The Syabru‐Bensi hydrothermal system in central Nepal: 2. Modeling and significance of the radon signature

Girault

Perrier

2014

JGR Solid Earth

View full text Add to dashboard Cite

The Syabru-Bensi hydrothermal system (SBHS), located in the Nepal Himalayas, is characterized by numerous hot (>30°C) springs and the release of dry, cold (<35°C) CO 2 associated with radon-222, detailed in the companion paper. In the SBHS, CO 2 and radon fluxes on the ground vary over 5-6 orders of magnitude, reaching exceptional mean values of 100 kg m À2 d À1 and 12 Bq m À2 s À1 , respectively. This paper extends the companion paper by developing three quantitative models for the radon signature of CO 2 based on measurements of radon and radium concentrations in the spring waters and effective radium concentration of rocks and soils. The first model considers near-surface radon and CO 2 degassing from water, considered unlikely unless there exist currently unidentified large discharges of hydrothermal water. The second model considers CO 2 , arising from deeper hydrothermal sources, incorporating radon from shallow radium sources as it percolates upward toward the surface, considered more likely as a percolation depth of 100 m is sufficient to account for the observed radon discharge. The third model considers the observed peak radon concentrations in the gas zones and assumes that gaseous CO 2 can be transported from kilometer-scale depths through a fault network connected to the zones. This latter model affords the possibility that variations of physical parameters at depths associated with earthquake nucleation might be detectable at the surface. Gas-dominated transport might operate in other locations in Himalayas and elsewhere and may be an important aspect of the coupled mechanisms associated with seismically active orogens.

show abstract

“…Models such as discrete fracture networks (DFNs) may be used for estimating up-scaled 5 permeability (e.g. (Bigi et al, 2013;Min et al, 2004)) or for rock mechanics analysis (Harthong et al, 2012;Jing and Hudson, 2002), with applications, including understanding fluid flow in tight oil and gas reservoirs (Aydin, 2000) and hydrogeology (Comerford et al, 2018), and assessing rock strength for mine engineering (Mas Ivars et al, 2011). There are four fundamental methods of fracture data collection at outcrop analogues (summarised in sect.…”

Section: Introductionmentioning

confidence: 99%

How do we see fractures? Quantifying subjective bias in fracture data collection

Andrews¹,

Roberts²,

Shipton³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. The characterisation of natural fracture networks using outcrop analogues is important in understanding sub-surface fluid flow and rock mass characteristics in fractured lithologies. It is well known from decision-sciences that subjective bias significantly impacts the way data is gathered and interpreted. This study investigates the impact of subjective bias on fracture data collected using four commonly used approaches (linear scanlines, circular scanlines, topology sampling and window sampling) both in the field and in workshops using field photographs. Considerable variability is observed between each participant's interpretation of the same scanline, and this variability is seen regardless of geological experience. Geologists appear to be either focussing on the detail or focussing on gathering larger volumes of data, and this innate personality trait affects the recorded fracture network attributes. As a result, fracture statistics derived from the field data and which are often used as inputs for geological models, can vary considerably between different geologists collecting data from the same scanline. Additionally, the personal bias of geologists collecting the data affects the size (minimum length of linear scanlines, radius of circular scanlines or area of a window sample) required of the scanline that is needed to collect a statistically representative amount of data. We suggest protocols to recognise, understand and limit the effect of subjective bias on fracture data biases during data collection.

show abstract

CO2 flow through a fractured rock volume: Insights from field data, 3D fractures representation and fluid flow modeling

Cited by 27 publications

References 29 publications

Genetic algorithm for fitting a mixed Bingham distribution to 3D orientations: a tool for the statistical and paleostress analyses of fracture orientations

Genetic algorithm for fitting a mixed Bingham distribution to 3D orientations: a tool for the statistical and paleostress analyses of fracture orientations

The Syabru‐Bensi hydrothermal system in central Nepal: 2. Modeling and significance of the radon signature

How do we see fractures? Quantifying subjective bias in fracture data collection

Contact Info

Product

Resources

About