Content of PetroWiki is intended for personal use only and to supplement, not replace, engineering judgment. SPE disclaims any and all liability for your use of such content. Highest potential formations for water blocks are low pressure gas sands (;0.25 psi/ft pore pressure), with small pore throats ( 10 microns), lower permeability (;100 md), and when using water that has a surface tension about 50 dyne/cm.
Additional data are sometimes required as well, but typically not for natural gas reservoirs. Two petrophysical properties of interest in gas engineering work are the Klinkenberg effect and non-Darcy flow. Low-pressure (i.e., laboratory) measurements give rise to what is termed the Klinkenberg or "slippage" effect because the mean free path of gas molecules is approximately the same size as the pores in a reservoir rock, meaning that gas molecules are so far apart that the gas does not behave as a continuum fluid, resulting in erroneously high apparent permeability. The effective liquid permeability can be determined in the laboratory by measuring gas permeabilities at different average core pressures. A plot of yields an intercept equal to kl (Figure 1) of 24 md compared with 48 md at low pressure.
Many approaches to estimating permeability exist. Recognizing the importance of rock type, various petrophysical (grain size, surface area, and pore size) models have been developed. This page explores techniques for applying well logs and other data to the problem of predicting permeability [k or log(k)] in uncored wells. If the rock formation of interest has a fairly uniform grain composition and a common diagenetic history, then log(k)-Φ patterns are simple, straightforward statistical prediction techniques can be used, and reservoir zonation is not required. However, if a field encompasses several lithologies, perhaps with varying diagenetic imprints resulting from varying mineral composition and fluid flow histories, then the log(k)-Φ patterns are scattered, and reservoir zonation is required before predictive techniques can be applied.
Permeability values of rocks range over many factors of 10; therefore, permeability is plotted on a logarithmic scale. Values commonly encountered in petroleum reservoirs range from a fraction of a millidarcy to several darcies. This page discusses factors affecting permeability associated with different rock types. The log10(k)-Φ plot of Fig.1 shows four data sets from sands and sandstones, illustrating the reduction in permeability and porosity that occurs as pore dimensions are reduced with compaction and alteration of minerals (diagenesis). Porosity is reduced from a maximum of 52% in newly deposited sandstones to as low as 1% in consolidated sandstones.
Many theoretical models have been developed to predict or correlate specific physical properties of porous rock. Most theoretical models are built on simplified physical concepts: what are the properties of an ideal porous media. However, in comparison with real rocks, these models are always oversimplified (they must be, to be solvable). Most of these models are capable of "forward modeling" or predicting rock properties with one or more arbitrary parameters. However, as is typical in earth science, models cannot be inverted from measurements to predict uniquely real rock and pore-fluid properties.
This article describes the ways in which electromagnetic heating can be applied to a reservoir. As shown in Figure 1, Q(t), the time-dependent rate of production of a given reservoir with either horizontal or vertical wells, depends on the flow of oil through the reservoir and through the producing wells. In the reservoir, the flow is conditioned by a temperature-dependent viscosity, μ(T), porosity, permeability, and compressibility (Φ, k, and c). To a first approximation, the last three parameters are unchanged by the heating. Heating strongly affects the viscosity of the oil in the reservoir porous media and in the wells.
The Haft Kel field is located in Iran. Its Asmari reservoir structure is a strongly folded anticline that is 20 miles long by 1.5 to 3 miles wide with an oil column thickness of approximately 2,000 ft. The most probable original oil in place (OOIP) was slightly 7 109 stock tank barrels (STB) with about 200 million STB in the fissures; numerical model history matching resulted in a value of 6.9 109 STB. The matrix block size determined from cores and flowmeter surveys varied from 8 to 14 ft. The numerical simulation model considered matrix permeabilities from 0.05 to 0.8 md.
Permeability is one of the fundamental properties of any reservoir rock required for modeling hydrocarbon production. However, shale permeability is not yet fully understood because of the complexities involved in modeling flow through nanoscale throats. Historically, shale was thought to perform two key functions: act as a seal for conventional reservoirs and as a source rock for hydrocarbons. Recently, several shale formations have also proven to be major self-sourcing hydrocarbon reservoirs. Liquid production from numerous shale reservoirs confirmed shale as an important source of hydrocarbons and spurred a worldwide assessment of the production potential of shale.
The Kozeny-Carman equation is typically used to calculate the pressure drop of fluids when crossing a medium that typically includes consolidated grains of some sort. Certain single phase permeability models can be derived based on this equation. The problem of predicting permeability is one of selecting a model expressing k in terms of other, measurable rock properties. Historically, the first approaches were based on a tube-like model of rock pore space known as the Kozeny-Carman relationship. The derivation of this "equivalent channel model" has been reworked by Paterson and Walsh and Brace.