A practical approach to develop a proper anisotropic rock physics model for media comprising of multiple fracture sets in the absence of sophisticated laboratory/wireline data (original) (raw)
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Rudarsko-geološko-naftni zbornik, 2021
Fractured reservoirs have always been of interest to many researchers because of their complexities and importance in the oil industry. The purpose of the current study is to model the fractured reservoir based on geomechanical restoration. Our target is the Arab Formation reservoir which is composed of seven limestone and dolomite layers, separated by thin anhydrite evaporate rock. First of all, in addition to the intensity, the dip, and the azimuth of the fractures, the magnitude and the direction of the stresses are determined using wireline data e.g. photoelectric absorption factor (PEF), sonic density, neutron porosity, a dipole shear sonic imager (DSI), a formation micro imager (FMI), and a modular formation dynamics tester (MDT). Then, the seismic data are interpreted and the appropriate seismic attributes are selected. One of our extracted attributes was the ant tracking attribute which is used for identifying large-scale fractures. Using this data, fractures and faults can ...
Proceedings of SPE Annual Technical Conference and Exhibition, 2004
In this paper, we present a combined geological, geophysical and rock mechanics approach to natural fractured reservoir characterization. The local structure entropy analysis on 3D seismic data is used to detect distributions of fault and subfault systems. The curvature attribute along with modeled strain and stress field, constrained with the log data measuring P-and S-wave velocities and rock density and the inverted elastic modulus from pre-stack seismic data, reveal effects of the geological structure, bed thickness and lithology on fracturability of the reservoir layer. These analyses quantify the relationships between the geologic factors and rock fracturability and describe physically the weighting factors for geologic parameters in controlling the rock fracturing. The comparison of the seismic azimuthal analysis results to these of geological and rock mechanics modeling provides an opportunity to verify whether the seismic anisotropy derived from seismic data is caused by structure related natural fracture patterns or by other mechanisms. The consistency among different techniques provides the confidence in the interpretation of the distribution of fractures induced by structures. If azimuthal seismic attribute data can be combined, the application of this procedure results in the development of the fracture connectivity anisotropy by considering relationships between the present and palaeostress fields. In addition, the scale depend analysis technique in this approach can improve the ability to identify the distribution of fractures with multiple length scales. In this paper, case studies are used to illustrate applications of these technologies and their efficiency.
This paper describes a fracture characterization and modeling project in China. The fracture characterization uses different sources and different scales of fracture-related data including outcrop, core, log, seismic, drilling, well test and production data for fracture recognition and analysis (Prioul et al (2009) and Hirata, (1989)). Subsequently, in the fracture modeling phase, a geostatistical method-the discrete modeling approach-is utilized to integrate the data from the various fracture characterization results. The fracture modeling uses the fracture characteristic parameters and their corresponding distribution under the guidance of the regional fracture development background to build a discrete fracture network (DFN) (Figure 1). Figure 1: Fracture Characterization and Modeling Workflow Fracture Parameters Analysis A detailed analysis of multiple fracture-related data types was conducted to characterize the fracture properties. These results are presented below. Outcrop data Outcrop data can provide regional scale features in terms of fracture density, length, aperture, dip, azimuth, sets, type and connectivity. Fracture aperture was found to be mostly <0.5 mm and more than 50% were not filled. Fractures were of the types tensile, shear and tensile-shear, and had good connectivity. Core data Fracture aperture, dip, type, density, length, sets, connectivity, porosity and permeability information for the sampled zones at the well locations can be obtained from core data (Aguilera (1988) and Nelson (2000)). In the study area, the apertures were mainly half-filled or unfilled, high angle and secondarily oblique and net-shaped. All apertures were <1.0 mm. Image log analysis This unconventional log has the advantage of directly detecting the fracture properties. It could provide details of the fracture azimuth, dip, aperture, density, and types surrounding the wellbore (Hirata (1989)). It also determines the locations and depths for identified fractures. Interpretation results of the imaging log in the study area show that the target layer is fracture-developed, which effectively improves the reservoir permeability. Seismic data analysis Seismic data are usually used for characterizing the fracture information between the wells. These data can be used to identify faults and large fractures. The fracture orientation and density may be characterized through the extraction of attributes or curvature from the 3D seismic (Murray (1977), Wang et al (2014)). The seismic data for the study area are relatively poor in quality, but because of spatial coverage, they could be helpful in understanding the fractures in-between the wells. Therefore, seismic data are corrected using well data. Horizons are also corrected by reflection events and wells. Based on the corrections, various seismic curvature attributes are extracted. Using a combination of multi-attributes and other information such as faults and well data, the fractures are characterized in-between the wells. This will provide a constraint for the subsequent the three-dimensional fracture density distribution volume and ultimately for the discrete fracture model. In addition, according to the current interpretation of the boundary faults and the internal secondary faults in the study area, the impact of the large boundary faults and the small internal faults on the fractures is analyzed (Zhou (1998)) (Figure 2 and Figure 3). Drilling data analysis Information from drilling such as mud loss, oil content in cuttings, exceptionally high permeability or wellbore collapse information may indicate the presence and stress orientation of a fracture-developed zone. Although drilling information is merely qualitative, it provides first-hand information that indicates the fractures. Well testing data analysis Fluid and pressure tests reveal fracture information, especially indicating fluid conductivity of the fracture and matrix systems. Tracer tests can determine the total effective permeability, fracture permeability, skin effect and connectivity. Pressure buildup test or interference tests can decide the fracture length and connectivity.
Bulletin of the Geological Society of Malaysia, 2012
Fractured reservoirs are challenging to handle because of their high level of heterogeneity. In particular, natural fractures have a significant impact on well performance and water production. Therefore, understanding their significance through fracture characterization is helpful in well placement and field development. This paper presents a best practice methodology for building a 3D stochastic fracture model using a Middle Eastern tight carbonate field example. This model is generated through the analysis and integration of data including cores, borehole images (BHI), logs, mud losses, production logs, well test data and 3D seismic data. The impact of lithology on fracture occurrence was quantified based on rock-typing. Rock-types are distributed in a 3D geological model using a high resolution sequence stratigraphic framework. The length, dip angle and orientation of fractures, together with the shale content of the facies where they occur, were defined to sort the tectonic fractures from the non-tectonic (diagenetic) ones. It was found that multiple sets of tectonic diffuse fractures are generally associated with cleaner limestone units. Altogether, three sets of diffuse fractures were identified from BHI data: NE-SW, EW and NW-SE. In addition, large-scale fracture corridors, including sub-seismic faults identified from seismic analysis, were detected and calibrated with cores and BHI. The final model incorporates two scales of tectonic fractures with a direct bearing on field production behavior: diffuse fractures and large fracture corridors. Fracture calibration was performed using production logs and well production data. Permeability at wells was computed in the 3D fracture model and matched with real build-up data. These data were then used to propagate 3D fracture properties (fracture porosity, fracture permeability and equivalent block size) in the upscaled geological model, for constructing a full-field reservoir simulation model. Few changes of the fracture properties were needed to obtain a good history match, indicating that the fracture model produced is robust.
Energies, 2017
This paper presents an integrated approach of discrete fracture network modelling for a naturally fractured buried-hill carbonate reservoir in the Jingbei Oilfield by using a 3D seismic survey, conventional well logs, and core data. The ant tracking attribute, extracted from 3D seismic data, is used to detect the faults and large-scale fractures. Fracture density and dip angle are evaluated by observing drilling cores of seven wells. The fracture density distribution in spatiality was predicted in four steps; firstly, the ant tracking attribute was extracted as a geophysical log; then an artificial neural network model was built by relating the fracture density with logs, e.g., acoustic, gamma ray, compensated neutron, density, and ant tracking; then 3D distribution models of acoustic, gamma ray, compensated neutron and density were generated by using a Gaussian random function simulation; and, finally, the fracture density distribution in 3D was predicted by using the generated artificial neural network model. Then, different methods were used to build the discrete fracture network model for different types of fractures of which large-scale fractures were modelled deterministically and small-scale fractures were modelled stochastically. The results show that the workflow presented in this study is effective for building discrete fracture network models for naturally fractured reservoirs.
International Journal of Rock Mechanics and Mining Sciences, 2014
This paper aims to examine the validity of the discrete fracture network (DFN) method in representing a realistic two-dimensional fractured rock in terms of their geomechanical response to in-situ stresses and hydraulic behaviour in a steady state fluid field. First, a real fracture network is extracted from the geological map of an actual rock outcrop, which is termed the analogue fracture network (AFN). Multiple DFN realisations are created using the statistics of the analogue pattern. A conductivity parameter that was found to have a linear relationship with the conductivity of 2D fracture networks is included to further enhance network similarity. A series of numerical experiments are designed with far-field stresses applied at a range of angles to the rock domains and their geomechanical response is modelled using the combined finitediscrete element method (FEMDEM). A geomechanical comparison between the AFN and its DFN equivalents is made based on phenomena such as heterogeneity of fracture-dependent stress contours, sliding between pre-existing fracture walls, coalescence of propagating fractures and variability of aperture distribution. Furthermore, an indirect hydro-mechanical (HM) coupling is applied and the hydraulic behaviour of the porous rock models is investigated using the hybrid finite element-finite volume method (FEFVM). A further comparison is conducted focusing on the hydraulic behaviour of the AFN and DFNs under the effects of geomechanical changes. The results show that although DFNs may represent an AFN quite well for fixed mechanical conditions, such a representation may not be dependable if mechanical changes occur.
Journal of Petroleum Exploration and Production Technology
Understanding the fracture patterns of hydrocarbon reservoirs is vital in the Zagros area of southwest of Iran as they are strongly affected by the collision of the Arabian and Iranian plates. It is essential to evaluate both primary and secondary (fracture) porosity and permeability to understand the fluid dynamics of the reservoirs. In this study, we adopted an integrated workflow to assess the influence of various fracture sets on the heterogeneous carbonate reservoir rocks of the Cenomanian–Santonian Bangestan group, including Ilam and upper Sarvak Formations. For this purpose, a combination of field data was used including seismic data, core data, open-hole well-logs, petrophysical interpretations, and reservoir dynamic data. FMI interpretation revealed that a substantial amount of secondary porosity exists in the Ilam and Sarvak Formations. The upper interval of Sarvak 1-2 (3491 m to 3510 m), Sarvak 1-3 (3530 m to 3550 m), and the base of Sarvak 2-1 are the most fractured inte...
Characterizing production-induced anisotropy of fractured reservoirs having multiple fracture sets
Geophysical Prospecting, 2012
Since natural fractures in petroleum reservoirs play an important role in determining fluid flow during production, knowledge of the orientation and density of fractures is required to optimize production. This paper outlines the underlying theory and implementation of a fast and efficient algorithm for upscaling a Discrete Fracture Network (DFN) to predict the fluid flow, elastic and seismic properties of fractured rocks. Potential applications for this approach are numerous and include the prediction of fluid flow, elastic and seismic properties for fractured reservoirs, model-based inversion of seismic Amplitude Versus Offset and Azimuth (AVOA) data and the optimal placement and orientation of infill wells to maximize production. Given that a single fracture network may comprise hundreds of thousands of individual fractures, the sheer size of typical DFNs has tended to limit their practical applications. This paper demonstrates that with efficient algorithms, the utility of Discrete Fracture Networks can be extended far beyond mere visualization.
Fracture Characterization and Their Impact on the Field Development
2005
Fracture characterization is a biggest challenge for the geoscientists in clastic and nonclastic reservoirs. With the advancement of all technical capabilities, in the acquisition of surface and subsurface geological data, still it is extremely difficult to understand, characterize, and predict the distribution of fractures in a field. Image logs can successfully be used to locate and to provide directional trends of fractures near the wellbore. However, capturing all the fractures in one well and to predict their flow behavior can still be a challenge. In this paper, a case study of a fractured carbonate reservoir will be presented. The field is currently producing about 500 bbl of oil per day through fractures. Four wells have been drilled on the structure to drain the oil reserves. Water flooding is being carried out in the field for the last 9 years for pressure maintenance and now 80 % water is being produced. The reservoir has very low primary porosity and permeability, and the flow is through fractures only. Based on the fracture data of three wells, a new well was drilled, located ideally at a structurally higher position, in crestal area of the field. Image data showed abundance of fractures with different orientation in the well bore but the well didn't flow and that led to its suspension. In this study, fracture data from image logs is compared with outcrop analogs and seismic reflection and interpretation data. In this paper, limitation of the available information, importance of understanding the stress regime, integration of geological and geophysical data and lesson learned from the current evaluation of the fracture system and their impact on development of a field in Powar basin will be presented.
Journal of Geophysics and Engineering, 2015
Fractured reservoirs contain a large proportion of hydrocarbon reserves in the Middle East. In these types of reservoirs, a variety of fracture types and networks provide the required permeability for hydrocarbon storage and flow. Fractured reservoir characterization has been challenging to petroleum geoscientists and reservoir engineers in terms of developing new approaches in this direction. A variety of techniques have been developed in the literature to study the distribution and the impact of fracture pore types on reservoir characterization. However, such techniques are not suitable for subsurface cases where prediction of fractures become troublesome and each of the developed techniques has its own advantages and limitations. In this study, an integrated approach is proposed for fracture characterization by employing different sources of data including 3D seismic attributes, geomechanical parameters, unconventional logs (image log and nuclear magnetic response (NMR) log), velocity-deviation log (VDL), conventional well logs, and routine core analysis data. Based on the azimuths of horizontal principal stresses and natural fractures, location of the wells over the structure hanging wall is determined. Interpretation of the seismic profiles from the study area indicated a fault-related fold structure style with fault throws controlling the magnitude of curvature. Moreover, fracture distribution of the Asmari reservoir is predicted by using curvature attribute, geomechanical parameters and horizontal slices of VDL. It seems that fractures probably have a much higher distribution at zone 1 and zone 3 of the Asmari formation.