Analysis of Naturally Fractured Reservoirs From Conventional Well Logs(includes associated papers 6420 and 6421 )

Abstract

Methods are presented for detecting and evaluating naturally fracturedreservoirs from porosity (sonic, neutron, and density)and resistivitylogs. It is shown that the porosity exponent of a naturally fracturedreservoir is smaller than the porosity exponent of the matrix. Charts havebeen generated for estimating the porosity exponent for these reservoirsas a function of total porosity, matrix porosity, and matrix-porosity exponent. Introduction The principles for the techniques presented here weredescribed previously using sonic and resistivity logs.The approach followed in this study was to use empiricalequations that had been derived for granular mediain the hope that they could be useful in the analysis offractured reservoirs. It was anticipated that thisapproach would result in a distinctive means of detectingand evaluating fractured media. The purpose of thispaper is to extend the method to other porosity logs, and to present ways to estimate fracture and totalporosity from logs. A theoretical model composed of cubes" indicated that the double-porosity exponent, m, shouldbe relatively small(ranging from about 1.1 to 1.3) fornaturally fractured systems. Towle was apparently thefirst investigator to indicate the similarity of a synthetic pore system (represented by cubes with spaces inbetween) to a fracture-type system. However, this modelconsidered only fractured porosity (matrix porosity waszero). This paper analyzes the behavior of the porosityexponent, m, in a naturally fractured reservoir by meansof a double-porosity model. It is found that the value ofm is certainly small and may range somewhere betweenabout 1.1 and the porosity exponent value of the matrix, depending on the degree of fracturing of the formation.Consequently, it appears that a comparison of thedouble-porosity exponent, m, (obtained from logs) with the matrix-porosity exponent, mb, (determined in thelaboratory) gives a reliable way to detect naturallyfractured systems. Values of water saturation are determined using aparameter, P, derived originally for the analysis ofintergranular media, and extended in this study to analyzefractured media. This parameter is a function of formation resistivity and porosity tool response. It has been foundempirically that P has a square-root-normal distributionfor zones 100-percent saturated with water. Hydrocarbonzones deviate from this distribution. By determining themean value of P at a water saturation of 100 percent, it ispossible to evaluate the resistivity index, I, for hydrocarbonzones and, hence, the values of water saturation. Log Properties for Detecting FracturesState of the Art Sonic amplitude logs have been used extensively inattempts to detect fractures. When the acoustic velocitygenerated by a logging tool is recorded, four wave typescan be identified: a compressional wave, a shear wave, a fluid or water wave, and a low-velocity wave.Generally, the compressional wave has been found to beattenuated more by vertical and high-angle fractures, while the shear wave seems to be more sensitive tohorizontal and low-angle fractures. However, experience has indicated that this measurement is not universally applicable because changes in amplitude as largeas those caused by fractures can be produced byvariations in lithology and tool centralization; and because, in practice, there might be solid contact across thefractures, so that the degree of acoustic discontinuity isdiminished. JPT P. 764^

Pore fabric assignment using electrical conductivity of some Albian–Cenomanian sequences in north Eastern Desert, Egypt

“…From the literatures, m varies from slightly less than 1.0 up to 5.12 for well-consolidated rocks, as the lithology factor may reach high values up to 9.0 for Fig. 8 Dependence of the electric anisotropy λ E on a electric foliation F E and b electric lineation L E for the studied petrophysical facies Table 2 Petrophysical and electric pore fabric parameters for the studied Albian-Cenomanian facies in north Eastern Desert σ b bulk density, σ g grain density, ∅c connected porosity, F formation resistivity factor, F av average F, T electric tortuosity, F E electric foliation, L E electric lineation, λ E electric anisotropy carbonate rock samples (Wyble 1958;Aguilera 1976;Keller 1982;Jorgensen 1988;Salem and Chilingarian 1999;Nabawy 2013;Nabway and Kassab 2013). For the present samples, the relatively high a value for facies 1 may be attributed to its calcareous content, whereas the relatively low a value for facies 3 may be attributed to its clay content.…”

Porosity partitioning of a fractured granite basement (FGB) reservoir in the Cuu Long Basin, offshore Southern Vietnam

“…The porosity partitioning coefficient was previously mentioned by many researchers (e.g., Pirson, 1970;Aguilera, 1976;Tiab and Donaldson, 2004). Its application for a FGB reservoir by now has been very limited.…”

Geohydrodynamic properties of hydrogeological units in parts of Niger Delta, southern Nigeria

“…These factors include: hydraulic radius, specific surface area, geometry and angularity of formation matrix and nature of soil formation matrix, grain arrangement, ease of fluid flow on the pore channel and grain surface, anisotropy, and overburden pressure. High fracturing is inversely proportional to the value of cementation factor according to Aguilera (1976), and large pore leads to high cementation factor (Lucia, 1983). Large angularity of grains leads to higher values of cementation factor.…”

“…Olsen et al (2008) and Fadhil et al (2013) also summarised different models for cementation factor. In documented materials the general range of cementation factor spans between unity in loose and fractured rocks (Aguilera, 1976;Jorgensen, 1988) and 5.12 for dense, hard and well indurated formations (Wyble, 1958). Specifically, the estimated cementation factors for various petrofacies are 1.09, 1.3, 1.3-1.6, 1.5-2.3, 1.8-3.0 and 1.8-4.2, for porous dolomites, glass spheres, homogeneous clean sands, heterogeneous sediments, compacted sandstones and limestones and argillaceous sandstones and siltstones respectively (Kirsch, 2009;Fadhil et al, 2013).…”