Identifying Producing Horizons in Fractured Reservoirs a Far Field Acoustic Approach

2021 ◽  
Author(s):  
Samhita Hati ◽  
Hemlata Chawla ◽  
Arnab Ghosh ◽  
Udit Guru ◽  
Rakesh Guru

Abstract The present study attempts to use 3D slowness time coherence (STC) technique to characterize the far-field fractures based on the reflector locations and attributes such as the dip and azimuth of fractures. These, in integration with the rest of the available data are used to accurately characterize the producing horizons in fractured basement reservoirs. The first step of the workflow involves the generation of 2D image to see if there are evidences of near and far wellbore reflectors. Since this is subjective in nature and does not directly provide quantitative results for discrete reflections, a new automated sonic imaging technique – 3D slowness time coherence (STC), has been incorporated to address this challenge. This method complements the image by providing the dip and azimuth for each event. The 2D and 3D maps of the reflectors can be readily available to integrate with the interpretations provided by other measurements, to better correlate and map the producing horizons. A field example is presented from the western offshore, India in which a fractured basement reservoir was examined using 3D STC technique to provide insight to the near and far field fracture network around the borehole. Few of the interpreted fractures from the resistivity image and conventional sonic fracture analysis coincide with the far field 3D STC reflectors, indicated by significant acoustic impedance. Further, the zones where the near and far field events coincide, represent a producing horizon. Comparing the near wellbore structures from the borehole images with the reflectors identified through the far field sonic imaging workflow provides necessary information to confirm the structural setting and characteristics of fractures away from the borehole. For the present case, it indicates the continuity of the fracture network away from the wellbore and explains the possibility of high production from the reservoir horizon. This study opens new perspective for identifying and evaluating fractured basement reservoirs using the sonic imaging technique. As more wells are drilled, it will be possible to better correlate and map the producing horizons in the field. This will allow better planning of location of future wells and help in optimizing field economics. A robust, automated and synergistic approach is used to locate and characterize individual arrival events which allows a more reliable understanding of the fracture extent and geologic structures. The 2D and 3D visualizations/maps can be readily integrated with the interpretations provided by other measurements.

2009 ◽  
Vol 12 (03) ◽  
pp. 455-469 ◽  
Author(s):  
Alireza Jafari ◽  
Tayfun Babadagli

Summary Fracture-network mapping and estimation of its permeability constitute two major steps in static-model preparation of naturally fractured reservoirs. Although several different analytical methods were proposed in the past for calculating fracture-network permeability (FNP), different approaches are still needed for practical use. We propose a new and practical approach to estimate FNP using statistical and fractal characteristics of fracture networks. We also provide a detailed sensitivity analysis to determine the relative importance of fracture-network parameters on the FNP in comparison to single-fracture conductivity using an experimental-design approach. The FNP is controlled by many different fracture-network parameters such as fracture length, density, orientation, aperture, and single-fracture connectivity. Five different 2D fracture data sets were generated for random and systematic orientations. In each data set, 20 different combinations of fracture density and length for different orientations were tested. For each combination, 10 different realizations were generated. The length was considered as constant and variable. This yielded a total of 1,000 trials. The FNPs were computed through a commercial discrete-fracture-network (DFN) modeling simulator for all cases. Then, we correlated different statistical and fractal characteristics of the networks to the measured FNPs using multivariable-regression analysis. Twelve fractal (sandbox, box counting, and scanline fractal dimensions) and statistical (average length, density, orientation, and connectivity index) parameters were tested against the measured FNP for synthetically generated fracture networks for a wide range of fracture properties. All cases were above the percolation threshold to obtain a percolating network, and the matrix effect was neglected. The correlation obtained through this analysis using four data sets was tested on the fifth one with known permeability for verification. High-quality match was obtained. Finally, we adopted an experimental-design approach to identify the most-critical parameters on the FNP for different fracture-network types. The results are presented as Pareto charts. It is believed that the new method and results presented in this paper will be useful for practitioners in static-model development of naturally fractured reservoirs and will shed light on further studies on modeling and understanding the transmissibility characteristics of fracture networks. It should be emphasized that this study was conducted on 2D fracture networks and could be extended to 3D models. This, however, requires further algorithm development to use 2D fractal characteristics for 3D systems and/or development of fractal measurement techniques for a 3D system. This study will provide a guideline for this type of research.


2021 ◽  
Author(s):  
Márk Somogyvári ◽  
Mohammadreza Jalali ◽  
Irina Engelhardt ◽  
Sebastian Reich

<p>In fractured aquifers, the permeability of open fractures could change over time due to precipitation effects and hydrothermal mineral growth. These processes could lead to the clogging of individual fractures and to the complete rearrangement of flow and transport pathways. Existing fractured rock characterization techniques often neglect this dynamicity and treat the reconstruction as a static inversion problem. The dynamic changes then later added to the model as an independent forward modeling task. In this research we provide a new data assimilation-based methodology to monitor and predict the dynamic changes of fractured aquifers due to mineralization in a quasi-real-time manner.</p><p>We formulate the inverse problem as a dynamic ‘hidden Markov process’ where the underlying model dynamicity is just partly known. Data assimilation methods are specifically designed to model such systems with strong uncertainties. A typical example for such problems is weather forecasting, where the combination of nonlinear processes and the partial observations make the forecasting challenging. To handle the strong random behavior, data assimilation approaches use stochastic algorithms. In this study we combine DFN-based stochastic aquifer reconstruction techniques with data assimilation algorithms to provide a dynamic inverse modelling framework for fractured reservoirs. We use the transdimensional DFN inversion of (Somogyvári et al., 2017) to initialize the data assimilation. This method uses a transdimensional MCMC approach to identify the most probable DFN geometries given the observations. Because the method is transdimensional it can adjust the number of model parameters, the number of fractures within the DFN. We developed this idea further by enhancing a particle filter algorithm with transdimensional model updates, allowing us to infer DFN models with changing fracture numbers.</p><p>We demonstrate the applicability of this new approach on outcrop-based synthetic fractured aquifer models. To create a dynamic DFN example, we simulate solute transport in a 2-D fracture network model using an advection-dispersion algorithm. We simulate fracture sealing in a stochastic way: we define a limit concentration above which the fractures could seal with a predefined probability at any timestep. At the initial timestep, a hydraulic tomography experiment is performed to capture the initial aquifer structure, which is then reconstructed by the transdimensional DFN inversion. At predefined timesteps hydraulic tests are performed at different parts of the aquifer, to obtain information about new state of the synthetic model. These observations are then processed by the data assimilation algorithm, which updates the underlying DFN models to better fit to the observations.</p>


SPE Journal ◽  
2016 ◽  
Vol 21 (04) ◽  
pp. 1140-1150 ◽  
Author(s):  
M. A. Fernø ◽  
J.. Gauteplass ◽  
M.. Pancharoen ◽  
A.. Haugen ◽  
A.. Graue ◽  
...  

Summary Foam generation for gas mobility reduction in porous media is a well-known method and frequently used in field applications. Application of foam in fractured reservoirs has hitherto not been widely implemented, mainly because foam generation and transport in fractured systems are not clearly understood. In this laboratory work, we experimentally evaluate foam generation in a network of fractures within fractured carbonate slabs. Foam is consistently generated by snap-off in the rough-walled, calcite fracture network during surfactant-alternating-gas (SAG) injection and coinjection of gas and surfactant solution over a range of gas fractional flows. Boundary conditions are systematically changed including gas fractional flow, total flow rate, and liquid rates. Local sweep efficiency is evaluated through visualization of the propagation front and compared for pure gas injection, SAG injection, and coinjection. Foam as a mobility-control agent resulted in significantly improved areal sweep and delayed gas breakthrough. Gas-mobility reduction factors varied from approximately 200 to more than 1,000, consistent with observations of improved areal sweep. A shear-thinning foam flow behavior was observed in the fracture networks over a range of gas fractional flows.


Geofluids ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Chuanyin Jiang ◽  
Xiaoguang Wang ◽  
Zhixue Sun ◽  
Qinghua Lei

We investigated the effect of in situ stresses on fluid flow in a natural fracture network. The fracture network model is based on an actual critically connected (i.e., close to the percolation threshold) fracture pattern mapped from a field outcrop. We derive stress-dependent fracture aperture fields using a hybrid finite-discrete element method. We analyze the changes of aperture distribution and fluid flow field with variations of in situ stress orientation and magnitude. Our simulations show that an isotropic stress loading tends to reduce fracture apertures and suppress fluid flow, resulting in a decrease of equivalent permeability of the fractured rock. Anisotropic stresses may cause a significant amount of sliding of fracture walls accompanied with shear-induced dilation along some preferentially oriented fractures, resulting in enhanced flow heterogeneity and channelization. When the differential stress is further elevated, fracture propagation becomes prevailing and creates some new flow paths via linking preexisting natural fractures, which attempts to increase the bulk permeability but attenuates the flow channelization. Comparing to the shear-induced dilation effect, it appears that the propagation of new cracks leads to a more prominent permeability enhancement for the natural fracture system. The results have particularly important implications for predicting the hydraulic responses of fractured rocks to in situ stress fields and may provide useful guidance for the strategy design of geofluid production from naturally fractured reservoirs.


2020 ◽  
Vol 8 (11) ◽  
pp. 4025-4042
Author(s):  
Zhiqiang Li ◽  
Zhilin Qi ◽  
Wende Yan ◽  
Xiaoliang Huang ◽  
Qianhua Xiao ◽  
...  

2020 ◽  
Author(s):  
Simon Oldfield ◽  
Mikael Lüthje ◽  
Michael Welch ◽  
Florian Smit

<p>Large scale modelling of fractured reservoirs is a persistent problem in representing fluid flow in the subsurface. Considering a geothermal energy prospect beneath the Drenthe Aa area, we demonstrate application of a recently developed approach to efficiently predict fracture network geometry across an area of several square kilometres.</p><p>Using a strain based method to mechanically model fracture nucleation and propagation, we generate a discretely modelled fracture network consisting of individual failure planes, opening parallel and perpendicular to the orientation of maximum and minimum strain. Fracture orientation, length and interactions vary following expected trends, forming a connected fracture network featuring population statistics and size distributions comparable to outcrop examples.</p><p>Modelled fracture networks appear visually similar to natural fracture networks with spatial variation in fracture clustering and the dominance of major and minor fracture trends.</p><p>Using a network topology approach, we demonstrate that the predicted fracture network shares greater geometric similarity with natural networks. Considering fluid flow through the model, we demonstrate that hydraulic conductivity and flow anisotropy are strongly dependent on the geometric connection of fracture sets.</p><p>Modelling fracture evolution mechanically allows improved representation of geometric aspects of fracture networks to which fluid flow is particularly sensitive. This method enables rapid generation of discretely modelled fractures over large areas and extraction of suitable summary statistics for reservoir simulation. Visual similarity of the output models improves our ability to compare between our model and natural analogues to consider model validation.</p>


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