This paper presents an innovative and promising, multi-discipline integrated approach that includes geology (BHI, cores, wireline logs), geophysics (seismic facies analysis), and reservoir engineering data (production data, PLT, welltest) that were combined to identify the main types of fractures, to predict their occurrence in the reservoir and to determine the hydraulic properties of the different fractures sets The Najmah - Sargelu of West Kuwait is an oil bearing reservoir made of tight carbonates where porosity and permeability is mainly provided by the fracture network. In this paper, we will first introduce the method used to identify and predict the two main scales of fractures: joints and large-scale fractures (faults and fracture swarms). The shale content (Vshale) and mechanical beds thickness were found to be the two main geological drivers on joints occurrence. Thickness of individual beds were recorded from BHI acoustic images which enabled to measure an S/T ratio (fracture spacing to bed thickness) for each fracture set and for different shalyness. Secondly, we used an innovative solution to deliver an accurate map of large-scale fractures location. This approach uses concurrently a set of selected fracture relevant attributes in a multi-variable statistical process called Seismic Facies Analysis (SFA). A 3D stochastic fracture model was then generated incorporating the two scales of fractures and constrained by the reservoir shalyness, the S/T ratio and the seismic facies map. The calibration of the hydraulic properties of the fractures was achieved through the second innovation presented in this paper: the simulation of a synthetic well test using the 3D fracture model and matched with the real data. This resulted in the calibration of the hydraulic fractures conductivity for each fracture type. These values were combined with the 3D stochastic fracture model to produce 3D fracture properties models (porosity, permeabilities and block size) for the Najmah - Sargelu of West Kuwait. Introduction A detailed geological and hydraulic characterisation of the fracture network occurring within the Upper Jurassic Najmah - Sargelu reservoir of West Kuwait was planned in 2003–2004 by Kuwait Oil Company (KSC). The objective of the study was to identify the main geological drivers on natural fractures occurence, to measure their hydraulic properties and eventually using discrete fracture modeling (DFN) approach to compute the equivalent fracture properties (porosity, permeability and block sizes) required for the reservoir simulation. This was achieved through a close integration of geological, geophysical, petrophysical and dynamic data carried out using workflows and methods implemented in a fracture analysis and modeling software (see Ref. 1). The main tasks performed during the project and presented in this paper are the following:Fracture analysis from coresFracture analysis from BHI logsIntegration of 3D seismic data set3D fracture modelingHydraulic characterization of the fracture networkComputation of the fracture properties in the reservoir grids Background The study area is approx. 2000 Km[2] and covers four fields namely A, B, C and D from North to South, (Fig. 1). The structure of the reservoir is characterized by gentle, rather elongated anticlines plunging mainly in the NNE and SSW directions at A, B and D fields. Field C and the west branch of field D are NNW - SSE oriented. The Top reservoir depth ranges between 11,000ft to 12,000ft.

This paper presents an innovative and promising, multidisciplinary approach that includes geology (borehole images, cores, and wireline logs); geophysics (seismic facies analysis), and reservoir engineering data (production data, production logs, and well test) that were combined to identify the main types of fractures, to predict their occurrence in the reservoir, and to determine the hydraulic properties of the different fractures sets.The Najmah-Sargelu of west Kuwait is an oil-bearing reservoir made of tight carbonates where porosity and permeability are provided mainly by the fracture network. In this paper, we first introduce the method used to identify and predict the two main scales of fractures: joints and large-scale fractures (faults and fracture swarms). The shale content (V shale ) and mechanical-beds thickness were found to be the two main geological drivers on joints occurrence. The thickness of individual beds was recorded from borehole acoustic images, which enabled us to measure a fracture spacing/bed thickness (S/T) ratio for each fracture set and for different shaliness. Second, we used an innovative solution to deliver an accurate map of the location of large-scale fractures. This approach concurrently uses a set of relevant attributes per selected fracture in a multivariable statistical process called seismic facies analysis (SFA).A 3D-stochastic fracture model was then generated, incorporating the two scales of fractures and this model was constrained by the shaliness of the reservoir, the S/T ratio, and the seismic facies map. In this approach, the two scales of fractures are modeled independently. The model of large-scale fractures is conditioned by the picking of lineaments on the SFA map and validated at wells, whereas small-scale fractures are modeled according to geological driven statistics on fracture density and fracture orientation. The calibration of the hydraulic properties of the fractures was achieved through the second innovation presented in this paper: the simulation of a synthetic well test using the 3D-fracture model and matched with the real data. This resulted in the calibration of effective hydraulic conductivity for each fracture type. These values were combined with the 3D-stochastic fracture model to produce 3D-fracture-properties models (porosity, permeability, and block size) for the Najmah-Sargelu.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper presents an innovative and promising, multidiscipline integrated approach that includes geology (BHI, cores, wireline logs), geophysics (seismic facies analysis), and reservoir engineering data (production data, PLT, welltest) that were combined to identify the main types of fractures, to predict their occurrence in the reservoir and to determine the hydraulic properties of the different fractures setsThe Najmah -Sargelu of West Kuwait is an oil bearing reservoir made of tight carbonates where porosity and permeability is mainly provided by the fracture network. In this paper, we will first introduce the method used to identify and predict the two main scales of fractures: joints and largescale fractures (faults and fracture swarms). The shale content (Vshale) and mechanical beds thickness were found to be the two main geological drivers on joints occurrence. Thickness of individual beds were recorded from BHI acoustic images which enabled to measure an S/T ratio (fracture spacing to bed thickness) for each fracture set and for different shalyness. Secondly, we used an innovative solution to deliver an accurate map of large-scale fractures location. This approach uses concurrently a set of selected fracture relevant attributes in a multi-variable statistical process called Seismic Facies Analysis (SFA).A 3D stochastic fracture model was then generated incorporating the two scales of fractures and constrained by the reservoir shalyness, the S/T ratio and the seismic facies map. The calibration of the hydraulic properties of the fractures was achieved through the second innovation presented in this paper: the simulation of a synthetic well test using the 3D fracture model and matched with the real data. This resulted in the calibration of the hydraulic fractures conductivity for each fracture type. These values were combined with the 3D stochastic fracture model to produce 3D fracture properties models (porosity, permeabilities and block size) for the Najmah -Sargelu of West Kuwait.

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