|Theme||Visible||Selectable||Appearance||Zoom Range (now: 0)|
The Kuparuk River oil field is west of the supergiant Prudhoe Bay oil field on Alaska's North Slope and was discovered in 1969. It has approximately 5.9 billion bbl of stock tank original oil in place (STOOIP) and covers more than 200 sq. The sandstone reservoir consists of two zones [A (62% of STOOIP) and C (38% of STOOIP)] that are separated by impermeable shales and siltstones. Sales oil is approximately 24 API with a viscosity at reservoir conditions of approximately 2.5 cp. The reservoir oil was approximately 300 to 500 psi undersaturated at the original reservoir pressure of approximately 3,300 psia.
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.
The Empire Abo field, located in New Mexico, US, covers 11,000 acres (12.5 miles long by 1.5 miles wide) and contains approximately 380 million stock tank barrels (STB) of original oil in place (OOIP). This reservoir is a dolomitized reef structure (Figure 1) with a dip angle of 10 to 20 from the crest toward the fore reef. The oil column is approximately 900 ft thick, but the average net pay is only 151 ft thick. The pore system of this reservoir is a network of vugs, fractures, and fissures because the primary pore system has been so altered by dolomitization; the average log-calculated porosity was 6.4% BV. Numerical simulations of field performance and routine core analysis data have indicated that the horizontal and vertical permeabilities are about equal.
Estimating resource and reserves crosses the disciplines between geoscientists and petroleum engineers. While the geoscientist may well have primary responsibility, the engineer must carry the resource and reserve models forward for planning and economics. Volumetric estimates of reserves are among the most common examples of Monte Carlo simulation. Consider the following typical volumetric formula to calculate the gas in place, G, in standard cubic feet. In this formula, there is one component that identifies the prospect, A, while the other factors essentially modify this component.
This page discusses various aspects of gas reservoir performance, primarily to determine initial gas in place and how much is recoverable. The equations developed can used to form the basis of forecasting future production rates by capturing the relationship between cumulative fluid production and average reservoir pressure. Material-balance equations provide a relationship between original fluids in place, cumulative fluid production, and average reservoir pressure. This equation is the basis for the p/z-vs.-Gp Reservoir engineers have often used pressure contour maps or some approximate methods to determine field average reservoir pressure for p/z analysis. Usually, however, individual well pressures are based on extrapolation of pressure buildup tests or from long shut-in periods. In either case, the average pressure measured does not represent a point value, but rather is the average value within the well's effective drainage volume (see Estimating drainage shapes).
Oil reservoirs are classified according to their fluid type. There are three broad oil classes. In order of increasing molecular weight, they are volatile oil, black oil, and heavy oil. Heavy-oil reservoirs are of minor interest during pressure depletion because they typically yield only marginal amounts of oil because of their low dissolved-gas contents and high fluid viscosities. The distinguishing characteristic between volatile and black oils is the stock-tank-oil content of their equilibrium gases.
If least-squares linear regression is used to compute N in Step 5, an equation analogous to Eq. 17 is used (where Eow is substituted for Eowf). This solution method is iterative because the material-balance error must be minimized. This calculation is carried out with a trial-and-error method or a minimization algorithm. Least-squares linear regression and minimization algorithms have become standard features in commercial spreadsheets.
For the effects of gravity segregation to be important, however, the well spacing may need to be prohibitively large or the producing rate may need to be prohibitively low. In such reservoirs, the vertical permeability is not high enough to permit much gravity segregation. The likely role of gravity segregation can be measured in terms of a gravity number, Ng. Ng is defined as the ratio of the time it takes a fluid to move from the drainage radius to the wellbore to the time it takes a fluid to move from the bottom of the reservoir to the top.