scholarly journals Multiscale Fracture Analysis in a Reservoir-Scale Carbonate Platform Exposure (Sorrento Peninsula, Italy): Implications for Fluid Flow

Geofluids ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
L. Massaro ◽  
A. Corradetti ◽  
F. Vinci ◽  
S. Tavani ◽  
A. Iannace ◽  
...  
Keyword(s):  
3D Model ◽  
Carbonate Platform ◽  
Fracture Network ◽  
Burial History ◽  
Southern Apennines ◽  
Discrete Fracture ◽  
Permeability Distribution ◽  
Relationship Of ◽  
Stochastic Distribution ◽  
Dfn Model

We derive the discrete fracture network (DFN) of a Lower Cretaceous carbonate platform succession exposed at Mt. Faito (Southern Apennines), which represents a good outcrop analogue of the coeval productive units of the buried Apulian Platform in the Basilicata oilfields. A stochastic distribution of joints has been derived by sampling at two different scales of observation. At the outcrop scale, we measured fracture attributes by means of scan lines. At a larger scale, we extracted fracture attributes from a 3D model. This multiscale survey showed the occurrence of an arresting bed for through-going fractures, which is characterized by a low relative permeability, determining a vertical compartmentalization. The DFN model, obtained by integrating fieldwork and numerical modelling by means of the 3D-Move® software, shows a well-defined relationship of permeability and fracture porosity with the relative connectivity of the fracture network. The latter is influenced by the length and aperture and to a lesser extent by the fracture intensity. The permeability distribution obtained for our outcrop analogue can be used to inform modelling of the Basilicata oilfield reservoirs, although the different burial history between the exposed Apennine Platform and the buried Apulian Platform must be taken into account.

Microseismicity-constrained discrete fracture network models for stimulated reservoir simulation

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. B37-B47 ◽  
Author(s):  
Sherilyn Williams-Stroud ◽  
Chet Ozgen ◽  
Randall L. Billingsley
Keyword(s):  
Hydraulic Fracture ◽  
Fracture Network ◽  
Discrete Fracture Network ◽  
Three Dimensions ◽  
Fracture Flow ◽  
Signal To Noise ◽  
Discrete Fracture ◽  
Microseismic Events ◽  
The Impact ◽  
Dfn Model

The effectiveness of hydraulic fracture stimulation in low-permeability reservoirs was evaluated by mapping microseismic events related to rock fracturing. The geometry of stage by stage event point sets were used to infer fracture orientation, particularly in the case where events line up along an azimuth, or have a planar distribution in three dimensions. Locations of microseismic events may have a higher degree of uncertainty when there is a low signal-to-noise ratio (either due to low magnitude or to propagation effects). Low signal-to-noise events are not as accurately located in the reservoir, or may fall below the detectability limit, so that the extent of fracture stimulated reservoir may be underestimated. In the Bakken Formation of the Williston Basin, we combined geologic analysis with process-based and stochastic fracture modeling to build multiple possible discrete fracture network (DFN) model realizations. We then integrated the geologic model with production data and numerical simulation to evaluate the impact on estimated ultimate recovery (EUR). We tested assumptions used to create the DFN model to determine their impact on dynamic calibration of the simulation model, and their impact on predictions of EUR. Comparison of simulation results, using fracture flow properties generated from two different calibrated DFN scenarios, showed a 16% difference in amount of oil ultimately produced from the well. The amount of produced water was strongly impacted by the geometry of the DFN model. The character of the DFN significantly impacts the relative amounts of fluids produced. Monitoring water cut with production can validate the appropriate DFN scenario, and provide critical information for the optimal method for well production. The results indicated that simulation of enhanced permeability using induced microseismicity to constrain a fracture flow property model is an effective way to evaluate the performance of reservoirs stimulated by hydraulic fracture treatments.

Construction of 3D Discrete Fracture Network Model using Structural and Hydrogeological Data

2020 ◽  
Author(s):  
Mohammadreza Jalali ◽  
Zhen Fang ◽  
Pooya Hamdi
Keyword(s):  
Rock Mass ◽  
Network Model ◽  
Fracture Network ◽  
Crystalline Rock ◽  
Discrete Fracture Network ◽  
Seismic Survey ◽  
Discrete Fracture ◽  
Dfn Model ◽  
Hydrogeological Data

<p>The presence of fractures and discontinuities in the intact rock affects the hydraulic, thermal, chemical and mechanical behavior of the underground structures. Various techniques have been developed to provide information on the spatial distribution of these complex features. LIDAR, for instance, could provide a 2D fracture network model of the outcrop, Geophysical borehole logs such as OPTV and ATV can be used to investigate 1D geometrical data (i.e. dip and dip direction, aperture) of the intersected fractures, and seismic survey can mainly offer a large structure distribution of the deep structures. The ability to combine all the existing data collected from various resources and different scales to construct a 3D discrete fracture network (DFN) model of the rock mass allows to adequately represent the physical behavior of the interested subsurface structure.</p><p>In this study, an effort on the construction of such a 3D DFN model is carried out via combination of various structural and hydrogeological data collected in fractured crystalline rock. During the pre-characterization phase of the In-situ Stimulation and Circulation (ISC) experiment [Amann et al., 2018] at the Grimsel Test Site (GTS) in central Switzerland, a comprehensive characterization campaign was carried out to better understand the hydromechanical characteristics of the existing structures. The collected multiscale and multidisciplinary data such as OPTV, ATV, hydraulic packer testing and solute tracer tests [Jalali et al., 2018; Krietsch et al., 2018] are combined, analyzed and interpreted to form a combined stochastic and deterministic DFN model using the FracMan software [Golder Associates, 2017]. For further validation of the model, the results from in-situ hydraulic tests are used to compare the simulated and measured hydraulic responses, allowing to evaluate whether the simulated model could reasonably represent the characteristics of the fracture network in the ISC experiment.</p><p> </p><p><strong>References</strong></p><ul><li>Amann, F., Gischig, V., Evans, K., Doetsch, J., Jalali, M., Valley, B., Krietsch, H., Dutler, N., Villiger, L., Brixel, B., Klepikova, M., Kittilä, A., Madonna, C., Wiemer, S., Saar, M.O., Loew, S., Driesner, T., Maurer, H., Giardini, D., 2018. The seismo-hydromechanical behavior during deep geothermal reservoir stimulations: open questions tackled in a decameter-scale in situ stimulation experiment. Solid Earth 9, 115–137.</li> <li>Golder Associates, 2017. FracMan User Documentation.  Golder Associates Inc, Redmond WA.</li> <li>Krietsch, H., Doetsch, J., Dutler, N., Jalali, M., Gischig, V., Loew, S., Amann, F., 2018. Comprehensive geological dataset describing a crystalline rock mass for hydraulic stimulation experiments. Scientific Data 5, 180269.</li> <li>Jalali, M., Klepikova, M., Doetsch, J., Krietsch, H., Brixel, B., Dutler, N., Gischig, V., Amann, F., 2018. A Multi-Scale Approach to Identify and Characterize the Preferential Flow Paths of a Fractured Crystalline Rock. Presented at the 2<sup>nd</sup> International Discrete Fracture Network Engineering Conference, American Rock Mechanics Association.</li> </ul>

A FRACTAL DISCRETE FRACTURE NETWORK MODEL FOR HISTORY MATCHING OF NATURALLY FRACTURED RESERVOIRS

Fractals ◽  
2019 ◽  
Vol 27 (01) ◽  
pp. 1940008 ◽  
Author(s):  
LIMING ZHANG ◽  
CHENYU CUI ◽  
XIAOPENG MA ◽  
ZHIXUE SUN ◽  
FAN LIU ◽  
...  
Keyword(s):  
History Matching ◽  
Fractured Reservoirs ◽  
Fracture Network ◽  
Naturally Fractured Reservoirs ◽  
Production Data ◽  
Multi Scale ◽  
Complex Fracture ◽  
Discrete Fracture ◽  
Dfn Model ◽  
Dimensional Optimization

The distribution of fractures is highly uncertain in naturally fractured reservoirs (NFRs) and may be predicted by using the assisted-history-matching (AHM) that calibrates the reservoir model according to some high-quality static data combined with dynamic production data. A general AHM approach for NFRs is to construct a discrete fracture network (DFN) model and estimate model parameters given the observations. However, the large number of fractures prediction required in the AHM process could pose a high-dimensional optimization problem. This difficulty is particularly challenging when the fractures form a complex multi-scale fracture network. We present in this paper an integrated AHM approach of NFRs to tackle these challenges. Two essential ingredients of the method are (1) a 2D fractal-DFN model constructed as the geological simulation model to describe the complex fracture network, and (2) a mixture of multi-scale parameters, built according to the fractal-DNF model, as an inversion parameter model to alleviate the high-dimensional optimization burden caused by complex fracture networks. A reservoir with a multi-scale fracture network is set up to test the performance of the proposed method. Numerical results demonstrate that by use of the proposed method, the fractures well recognized by assimilating production data.

scholarly journals Developing a new algorithm for numerical modeling of discrete fracture network (DFN) for anisotropic rock and percolation properties

2021 ◽  
Vol 11 (2) ◽  
pp. 839-856
Author(s):  
Erfan Hosseini ◽  
Mohammad Sarmadivaleh ◽  
Zhongwei Chen
Keyword(s):  
Fractured Rock ◽  
Fracture Network ◽  
Connected Components ◽  
Threshold Condition ◽  
Fracture Density ◽  
Anisotropic Rock ◽  
Fracture Properties ◽  
Fracture Length ◽  
Discrete Fracture ◽  
Dfn Model

AbstractThe role of natural fractures in future reservoir performance is prominent. The fractured porous media is composed of an interconnected network of fractures and blocks of the porous medium where fractures occur in various scales and have a strong influence either when most of the flow is concentrated and them or when they act as barriers. A general numerical model for discrete fracture networks (DFN) is usually employed to handle the observed wide variety of fracture properties and the lack of direct fracture visualization. These models generally use fracture properties’ stochastic distribution based on sparse and seismic data without any physical model constraint. Alternatively, a DFN model includes usual numerical geomechanical approaches like boundary element and finite element. But here, a geostatistical methodology has been used to generate a DFN model. In this paper, an alternative modeling technique is employed to create the realization of an anisotropic fractured rock using simulated annealing (SA) optimization algorithm. There is a notable positive correlation between fracture length and position. There are three principal subjects in a study of fractured rocks. Firstly, the network’s connectivity, secondly, fluid flows through the system, and thirdly, dispersion. Here, connectivity of generated networks is considered. Continuum percolation is the mathematical model to study the geometry of connected components in a random subset of space. Different random realizations from the S.A. algorithm in four different sizes of L = 100, 150, 200, 250 at post-threshold condition are used as disordered media in percolation theory to compute percolation properties using Monte Carlo simulation. The percolation threshold (critical fracture density) and two crucial scaling exponents (β and υ) that dictate the model’s connectivity behavior are estimated to over 200 realizations.

Discrete fracture network of the Latemar carbonate platform

2015 ◽  
Vol 134 (3) ◽  
pp. 474-494 ◽  
Author(s):  
Sabina Bigi ◽  
Mariangela Marchese ◽  
Marco Meda ◽  
Sergio Nardon ◽  
Marco Franceschi
Keyword(s):  
Carbonate Platform ◽  
Fracture Network ◽  
Discrete Fracture Network ◽  
Discrete Fracture
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