Use of Transient Rate and Pressure Data To Determine Drainage Area Average Reservoir Pressure Without Shutting In the Well

1994 ◽  
Author(s):  
Usman Ahmed
1978 ◽  
Vol 18 (02) ◽  
pp. 139-150 ◽  
Author(s):  
R. Raghavan ◽  
Nico Hadinoto

Abstract Analysis of flowing and shut-in pressure behavior of a fractured well in a developed live-spot fluid injection-production pattern is presented. An idealization of this situation, a fractured well located at the center of a constant pressure square, is discussed. Both infinite-conductivity and uniform-flux fracture cases are considered. Application of log-log and semilog methods to determine formation permeability, fracture length, and average reservoir pressure A discussed. Introduction The analysis of pressure data in fractured wells has recovered considerable attention because of the large number of wells bat have been hydraulically fractured or that intersect natural fractures. All these studies, however were restricted to wells producing from infinite reservoirs or to cases producing from infinite reservoirs or to cases where the fractured well is located in a closed reservoir. In some cases, these results were not compatible with production performance and reservoir characteristics when applied to fractured injection wells. The literature did not consider a fractured well located in a drainage area with a constant-pressure outer boundary. The most common example of such a system would be a fractured well in a developed injection-production pattern. We studied pressure behavior (drawdown, buildup, injectivity, and falloff) for a fractured well located in a region where the outer boundaries are maintained at a constant pressure. The results apply to a fractured well in a five-slot injectionproduction pattern and also should be applicable to a fractured well in a water drive reservoir. We found important differences from other systems previously reported. previously reported. We first examined drawdown behavior for a fractured well located at the center of a constant-pressure square. Both infinite-conductivity and uniform-flux solutions were considered. The drawdown solutions then were used to examine buildup behavior by applying the superposition concept. Average reservoir pressure as a function of fracture penetration ratio (ratio of drainage length to fracture length) and dimensionless time also was tabulated. This represented important new information because, as shown by Kumar and Ramey, determination of average reservoir pressure for the constant-pressure outer boundary system was not as simple as that for the closed case since fluid crossed the outer boundary in an unknown quantity during both drawdown (injection) and buildup (falloff). MATHEMATICAL MODEL This study employed the usual assumptions of a homogeneous, isotropic reservoir in the form of a rectangular drainage region completely filled with a slightly compressible fluid of constant viscosity. Pressure gradients were small everywhere and Pressure gradients were small everywhere and gravity effects were neglected. The outer boundary of the system was at constant pressure and was equal to the initial pressure of the system. The plane of the fracture was located symmetrically plane of the fracture was located symmetrically within the reservoir, parallel to one of the sides of the boundary (Fig. 1). The fracture extended throughout the vertical extent of the formation and fluid was produced only through the fracture at a constant rate. Both the uniform-flux and the infinite-conductivity fracture solutions were considered. P. 139


1969 ◽  
Vol 9 (03) ◽  
pp. 277-278
Author(s):  
A.S. Odeh ◽  
R. Al Hussainy

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


Author(s):  
Y., E. Sugiharto

Pressure analysis is concerned with the study of systematic variations of reservoir pore pressure with depth. The most common interpretation for pressure analysis is pressure-depth plot analysis, but other techniques that magnify understated pressure differences are also available. Formation pressure measurement is of immense value in quantitative evaluation and risking of prospects. Once the pressure data has been acquired, we need to understand how to interpret the data received because reservoir pressure data has numerous applications and interpreting it wrongly could make the results misleading. At equilibrium state (i.e. there are no net forces, and no acceleration), a fluid in the system is called hydrostatic equilibrium. Hydrostatic pressure increases with depth measured from the surface due to the increasing weight of fluid exerting downward force from above. The traditional pressure evaluation is usually done in conventional unit such as psi, kPa, psi/feet, psi/m, kPa/m, ppg. The current work will introduce the concepts and definitions of formation pressure evaluation using Pressure Index (PI) with the unit g/cc. For better understanding of the application of PI, some reservoir studies are also discussed in this paper.


2021 ◽  
Author(s):  
Saumitra Dwivedi ◽  
Guillaume Suzanne ◽  
Abdulhakim Algadban ◽  
Ibrahim A. Hameed

Abstract This paper aims to explore modern techniques based on artificial intelligence (AI) and data science, in order to produce data-driven workflows to analyze, model, and simulate reservoir pressure dynamics. In this paper, it was investigated a data-driven workflow to model reservoir pressure at any point in space and time from sparse pressure data observed at wells, without building a physics-based numerical model. This workflow was termed as spatiotemporal modelling of reservoir pressure. Spatiotemporal modelling of reservoir pressure was based on a three-step workflow including multivariate analysis of pressure data and relevant explanatory variables (features), pressure modelling and spatiotemporal interpolation. The overall workflow provided a comprehensive method to understand and map the reservoir pressure dynamics using data science tools. Several modelling techniques such as generalized additive models, artificial neural networks and spatiotemporal kriging were investigated for their applicability and accuracy. The workflow was applied to a real oil and gas reservoir case, for which the reservoir pressure prediction accuracy was optimized through a few experiments. The optimum experiment produced highly accurate prediction with a mean absolute error of 26.85 psi measured on the training dataset. Moreover, a portion of data used was kept to evaluate blind test accuracy, which amounted to a mean absolute error of 55 psi, for the optimum case. The proposed data-driven workflow was aimed to improve current methods of reservoir engineering and simulation. The suggested workflow showed high accuracy in reservoir pressure predictions with high efficiency in terms of computational resources and time. Additionally, the proposed workflow was developed using open-source libraries which pose no additional cost to computation, in contrast to extremely expensive industry standard physics-based reservoir simulation software. Finally, this workflow could also be used to model other reservoir variables such as production ratios (Water cut, and Gas-Oil Ratio), contacts (Water-Oil contact and Gas-Oil contact), among others.


Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1585-1587 ◽  
Author(s):  
Miodrag M. Roksandic

Hardage et al. (1994) conducted a study at Stratton Field with the purpose of detecting thin‐bed compartmented reservoirs in a fluvially deposited system (Oligocene Frio Formation), and rightly concluded that, in order to determine which seismically imaged stratigraphic changes are compartment boundaries, it is necessary to incorporate geologic and reservoir engineering data (particularly reservoir pressure data) into seismic interpretation. Their interpretation philosophy consisted of defining depositional stratal surfaces (I would rather say paleodepositional surfaces), and in analyzing seismic reflection amplitude behavior on such surfaces.


1999 ◽  
Vol 2 (01) ◽  
pp. 53-61 ◽  
Author(s):  
S.D. Coutts

Summary Planning for the depressurization of the Brent Field required an extensive study of the aquifer to determine the withdrawals necessary to depressurize the field and to predict the effect of depressurization on surrounding fields. Static and dynamic aquifer models were constructed and several techniques were applied to evaluate the sealing capacity of the major boundary fault. Since the aquifer extends over several license blocks, integration of a wide range of data of varying quality from different sources was required to build up a complete aquifer model. The results highlighted effects of pressure communication between fields which were not apparent to teams studying individual fields in isolation. Introduction Controlled depressurization of the Brent Field (Fig. 1) to maximize hydrocarbon recovery1,2 will require back production of considerable volumes of water to gradually reduce the reservoir pressure from 5500 to 1000 psi. An understanding of the size and strength of the aquifer attached to the reservoir (Fig. 2) is a critical input to the design of this process, influencing the rate and quantity of water to be back produced. In addition, other oil fields are thought to be in pressure communication with the Brent Field via the aquifer and the potential impact of Brent depressurization on all these fields needed to be quantified. Thus, as part of the planning for depressurization, an extensive integrated petroleum engineering study was undertaken to assess the range of uncertainties in the behavior of the Brent reservoir aquifer during depressurization and to quantify the possible impact of the redevelopment project on surrounding fields, including the effect of any possible communication between the Brent and Statfjord Fields. This study was confined to the Brent reservoir as the Statfjord reservoir aquifer has already been shown to be relatively tight, with the result that depressurization will have minimal impact on even the nearest fields. In fact, the gas reserves in the Statfjord in both the Brent South and Strathspey Fields are planned to be produced by depletion drive, allowing the reservoir pressure to drop until the wells die, without any voidage replacement. The investigation concentrated on three major aspects.An analysis of all available data to establish the extent of the aquifer in communication with the Brent Field and determine its properties.Prediction of the behavior of the aquifer during depressurization.An assessment of the risks of additional communication being established during depressurization, particularly by possible leakage across the Northern Boundary Fault from the Statfjord Field, and quantifying the impact of any such communication in the worst case. Extent and Properties of Brent Aquifer Since there is a general dearth of data in areas between fields, the study required integration of a wide variety of data from various sources to produce an overall aquifer description. Aquifer Mapping. Some base data were available from a limited series of time and reservoir property maps of the Brent and Statfjord Formations in the Greater Brent Area. These had been produced during an early review of the aquifer attached to the Statfjord Field. One initial task of the present study was thus to produce a depth map of the Brent Aquifer at top Brent reservoir level (Fig. 2). This was carried out by combining existing depth maps of known fields with a regional time map. The latter map was depth converted using available depth functions from the Brent Field itself, and tied in to all available wells within the aquifer. Over key areas, principally the Northern Boundary Fault area, all available seismic, both two dimensional (2D) and three dimensional (3D), was reevaluated to provide a consistent seismic interpretation. A set of cross sections over the aquifer is shown in Fig. 3. To the north, west and east the Brent aquifer is seen to be bounded by major faulting. To the south, in the area of North Alwyn, the aquifer is effectively bounded by a combination of faulting and poor quality reservoir. Historical Aquifer Pressure Data. All available Brent reservoir pressure data from wells in the Greater Brent area were collated and corrected to the Brent Field datum level of 8700 ftss for comparison. The data consisted of repeat formation tests (or equivalent) pressure data from exploration, appraisal and early development wells (Fig. 4), together with average pressure trends from the fields on production. The early data from the 1970s suffered from inaccuracies in both absolute pressure measurements from Amerada gauges and in true-vertical depth conversion, since full deviation surveys were not run in supposedly vertical wells. Representative average data were plotted against time for each cycle3 (Figs. 5 to 7), from which several conclusions were drawn:All fields in the Brent and Statfjord aquifer blocks were initially in the same pressure regime, which was some 100 psi below that in the Dunlin block to the west.Subsequent performance of the Brent and Statfjord Fields shows no evidence of any communication between the two blocks over producing times.All fields within the Brent aquifer block are in some degree of pressure communication. However, the downdip well 3/3-11, drilled in 1989, was still undepleted, indicating that faulting and permeability deterioration with depth severely limit the effective western extent of the aquifer.


Sign in / Sign up

Export Citation Format

Share Document