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Collaborating Authors
- Information Technology > Knowledge Management (0.40)
- Information Technology > Communications > Collaboration (0.40)
Rate transient analysis (RTA) is used routinely to analyze the production history of unconventional wells. Specifically, it is used to determine the time at the end of linear flow (time to depletion), estimate drainage volume, and predict the estimated ultimate recovery (EUR) of wells. RTA uses a rate-normalization technique to characterize how the well rate changes with a changing bottomhole flow pressure. However, rate normalization approximates a more-general technique known as pressure deconvolution.
Summary In this paper we propose an anisotropic dual poros - ity model to estimate reservoir parameters (includ - ing elastic parameters) in isotropic and anisotropic porous rocks. This method extends the clay -sand mixture model of Xu and White(1995) to anisotropic rocks using the equivalent medium theories proposed by Hornby et al. (1994). The method allows depth varying aspect ratios of clay particles and sand grains, and the core -log calibration plays an important role. Applying this method to the field data from the North Sea indicates that reservoir parameters can be satisfactorily obtained. Introduction Extensive theoretical work and laboratory experiments have been devoted to estimate reservoir parameters in isotropic and anisotropic porous rocks. Various empirical and theoretical models have been proposed. However, all of them are used under limited conditions based on different assumptions for practical application.
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Reservoir Characterization (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (0.40)
- Reservoir Description and Dynamics > Fluid Characterization > Fluid modeling, equations of state (0.40)
This reference is for an abstract only. A full paper was not submitted for this conference. A good understanding of reservoir performance for management and production requires information on the pressure and saturation variations together with the major connected paths in the system. However in complex geological settings such as channelised turbidite sands, the pathways for fluid movement and pressure evolution between the individual sand bodies are not obvious and cannot be easily inferred from geological data. The effect of gas/water injection and production is therefore hard to predict with certainty. To address this problem, a method which integrates both time-lapse seismic data and a well interference test is developed to help provide a local update to the reservoir simulation model. The benefit is derived from the overlap between the aerial resolution of the time-lapse seismic with the harder, more localised pressure data from the well test. The seismic contributes to an understanding of the 3D geometry of the connected bodies, and this information is fed into an inversion of the well test data to help reduce the non-uniqueness in the interpretation and improve stability. The technique is successfully applied to a deepwater turbidite reservoir with satisfactory results.
- Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Seismic (four dimensional) monitoring (0.87)
- Reservoir Description and Dynamics > Reservoir Characterization > Exploration, development, structural geology (0.78)
In a recent paper, van Poollen et al. presented equations relating observed field pressures to those calculated by a numerical simulator. The equations are applicable to steady- and semi steady-state flow for wells draining circular areas and using an equivalent block radius. They implicitly assume that wells are located at the center of the drainage area. In this note we present equations that generalize the previous method and relate field to model pressures for various shapes of drainage area, well pressures for various shapes of drainage area, well location and grid configuration. Using the generalized equations of flow of Brons and Miller, and following a method of derivation similar to that reported by van Poollen et al., we obtain:For steady-state flow: .................(1) For semisteady-state flow: ...................(2) For unsteady-state flow: .....................(3) where subscripts m and f refer to the model and field, respectively, and P D theta of Eq. 3 is the dimensionless initial pressure. For a circular system A pi r, and CA = 31.6 from Ref. 3. If we substitute these values in Eqs. 1 and 2, we obtain the results of van Poollen et al. as represented by their Eqs. 14a and 14b. In a manner analogous to that of van Poollen et al. the average reservoir pressure can be related to the dynamic pressure by using a dimensionless time based on the drainage area A rather than radius. Also, the relation between the average reservoir pressure and the simulator pressure in Eqs. 1 and 2 can be based on producing time as well as shut-in time, since it is possible to generate one method from the other as was shown by Ramey. NOMENCLATURE A = area in sq ftB = formation volume factor, res. bbl/STBCA = shape factorDD =c = compressibility, 1/psih = thickness, ftk = permeability, md PD, m, t = dimensionless model pressure, [141.2kb/ PD, m, t = dimensionless model pressure, [141.2kb/(q B)]P PD = dimensionless average reservoir pressure PD = dimensionless average reservoir pressure P = pressure, psiq = production rate, STB/Drw = well radius, ftt = flow time, days= porosity fraction= viscosity, cp P. 277