Enhanced Reservoir Description: Using Core and Log Data to Identify Hydraulic (Flow) Units and Predict Permeability in Uncored Intervals/Wells
- Jude O. Amaefule (Core Laboratories) | Mehmet Altunbay (Core Laboratories) | Djebbar Tiab (U. of Oklahoma) | David G. Kersey (Core Laboratories) | Dare K. Keelan (Core Laboratories)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 3-6 October, Houston, Texas
- Publication Date
- Document Type
- Conference Paper
- 1993. Society of Petroleum Engineers
- 5.8.6 Naturally Fractured Reservoir, 1.2.3 Rock properties, 5.1 Reservoir Characterisation, 5.6.1 Open hole/cased hole log analysis, 5.5.2 Core Analysis, 5.6.3 Deterministic Methods, 5.7 Reserves Evaluation, 1.8 Formation Damage, 2.4.3 Sand/Solids Control, 5.1.5 Geologic Modeling, 5.6.2 Core Analysis, 1.6.9 Coring, Fishing, 5.5 Reservoir Simulation, 4.3.4 Scale, 1.10.1 Drill string components and drilling tools (tubulars, jars, subs, stabilisers, reamers, etc), 5.8.7 Carbonate Reservoir, 5.1.4 Petrology, 5.7.4 Probabilistic Methods
- 53 in the last 30 days
- 5,845 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 8.50|
|SPE Non-Member Price:||USD 25.00|
Understanding complex variations in pore geometry within different lithofacies is the key to improved reservoir description and exploitation. Core data provide information on various depositional and diagenetic controls on pore geometry. Variations in pore geometrical attributes in turn, define the existence of distinct zones (hydraulic units) with similar fluid-flow characteristics. Classic discrimination of rock types has been based on subjective geological observations and on empirical relationships between the log of permeability versus porosity. However for any porosity within a given rock type, permeability can vary by several orders of magnitude, which indicates the existence of several flow units.
In this paper, a new, practical and theoretically correct methodology is proposed for identification and characterization of hydraulic units within mappable geological units (facies). The technique is based on a modified Kozeny-Carmen equation and the concept of mean hydraulic radius. The equation indicates that for any hydraulic unit, a log-log plot of a "Reservoir Quality Index," (RQI), which is equal to 0.0314 k/ , versus a "Normalized Porosity Index" ( x) which is equal to /(1- ) should yield a straight line with a unit slope. The intercept of the unit slope line with z= 1, designated as the "Flow Zone Indicator" (FZI), is a unique parameter for each hydraulic unit. RQI, z and FZJ are based on stressed porosity and permeability data measured on core samples.
FZI is then correlated to certain combinations of logging tool responses to develop regression models for permeability predictions in cored and uncored intervals or wells. The proposed technique has been successfully tested in clastic rocks from East Texas, South America, West Africa, South East Asia and Far East Asia, as well as carbonate sequences from West Texas and Canada. This paper documents the theoretical development, validates and characterizes the hydraulic units, and presents predicted versus actual permeability data to demonstrate the efficacy of the proposed technique.
One of the most important existing and emerging challenges of geoscientists and engineers is to improve reservoir description techniques. It is well recognized that improvements in reservoir description will reduce the amount of hydrocarbon left behind pipe. Accurate determination of pore-body/throat attributes and fluid distribution are central elements in improved reservoir description. Many reservoir description programs, though detailed, have not included descriptions at the pore-throat scale. Yet, pore-throat attributes control initial/residual hydrocarbon distribution and fluid flow. Because they are readily available, continuous sources of data, logging tool responses are often used to draw inferences about lithology, depositional and diagenetic sequences, and fluid content. These inferences are based on empirical models utilizing correlations among tool responses, rock and fluid properties. In many instances, unfortunately, the correlation models can not be used globally because of the influences of factors not fully considered by the models. Factors include (a) the presence of potassium-feldspar, zircon, etc. causing erroneously high calculated Vsh from the gamma ray; (b) microporosity in kaolinite, chert, etc. leading to high apparent water saturation calculations; and (c) siderite, pyrite, barite, and smectite influencing the resistivity, density and neutron log calculations.
|File Size||1 MB||Number of Pages||16|