The Interpretation of Reservoir Pressure Data in the Dunbar Field (UKCS)

1998 ◽  
Vol 1 (05) ◽  
pp. 384-391 ◽  
Author(s):  
Yann Bigno ◽  
J.M. Baillie ◽  
T.P. Coombes
Keyword(s):  
Reservoir Pressure ◽  
Pressure Data

Analysis of Pressure Data for Fractured Wells: The Constant-Pressure Outer Boundary

1978 ◽  
Vol 18 (02) ◽  
pp. 139-150 ◽  
Author(s):  
R. Raghavan ◽  
Nico Hadinoto
Keyword(s):  
Constant Pressure ◽  
Outer Boundary ◽  
Reservoir Pressure ◽  
Pressure Gradients ◽  
Pressure Data ◽  
Pressure Behavior ◽  
Fracture Length ◽  
Infinite Conductivity ◽  
Production Pattern ◽  
Fractured Well

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

Pressure Index (PI): A Novel Practical Method for Evaluating Pressure in Offshore Malaysia

2020 ◽  
Author(s):  
Y., E. Sugiharto
Keyword(s):  
Hydrostatic Pressure ◽  
Practical Method ◽  
Hydrostatic Equilibrium ◽  
Reservoir Pressure ◽  
Formation Pressure ◽  
Pressure Data ◽  
Pressure Index ◽  
Plot Analysis ◽  
Conventional Unit ◽  
Pressure Analysis

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.

Data-Driven Spatiotemporal Modeling of Reservoir Pressure Dynamics in a Giant Saturated Oil Field in Libya

2021 ◽  
Author(s):  
Saumitra Dwivedi ◽  
Guillaume Suzanne ◽  
Abdulhakim Algadban ◽  
Ibrahim A. Hameed
Keyword(s):  
Data Science ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Additive Models ◽  
Data Driven ◽  
Reservoir Pressure ◽  
Gas Oil ◽  
Pressure Data ◽  
Spatiotemporal Modelling ◽  
Pressure Dynamics

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.

On: “A 3-D seismic case history evaluating fluvially deposited thin‐bed reservoirs in a gas‐producing property,” by B. A. Hardage, R. A. Levey, V. Pendleton, J. Simmons, and R. Edsen (November 1994 GEOPHYSICS, 59, p. 1650–1665).

Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1585-1587 ◽  
Author(s):  
Miodrag M. Roksandic
Keyword(s):  
Case History ◽  
Seismic Reflection ◽  
Seismic Interpretation ◽  
Reservoir Engineering ◽  
Reservoir Pressure ◽  
Pressure Data ◽  
Reflection Amplitude ◽  
Engineering Data ◽  
Frio Formation

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.

Aquifer Behavior During Brent Depressurization and the Impact on Neighboring Fields

1999 ◽  
Vol 2 (01) ◽  
pp. 53-61 ◽  
Author(s):  
S.D. Coutts
Keyword(s):  
Extensive Study ◽  
Petroleum Engineering ◽  
Absolute Pressure ◽  
Reservoir Pressure ◽  
Pressure Data ◽  
Northern Boundary ◽  
Worst Case ◽  
Boundary Fault ◽  
Wide Range ◽  
The Impact

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.

A SCADA By-Pass Method to Bring Fiber-Optics Distributed Temperature and Reservoir Pressure Data to Reservoir Engineers!

2014 ◽  
Author(s):  
Ashish Chaudhary ◽  
Philippe Maguet ◽  
Graciela Eva Naveda ◽  
Zhang Leimin ◽  
Kueh Jing Zhi ◽  
...  
Keyword(s):  
Fiber Optics ◽  
Reservoir Pressure ◽  
Pressure Data

Pressure Buildup Equations for Spherical Flow Regime Problems

1974 ◽  
Vol 14 (06) ◽  
pp. 545-555 ◽  
Author(s):  
W.E. Culham
Keyword(s):  
Flow Regime ◽  
Transition Period ◽  
Oil Wells ◽  
Reservoir Pressure ◽  
Pressure Data ◽  
Pressure Buildup ◽  
Practical Utility ◽  
Straight Line ◽  
Practical Guidelines ◽  
Buildup Curve

Abstract Pressure buildup and flow tests conducted in wells that do not completely penetrate the producing formation or that produce from only a small portion of the total productive interval can generate noncylindrical flow regimes and require special interpretation procedures. Frequently a spherical flow regime is representative, and a new equation based on the continuous point-source solution to the diffusivity equation in spherical coordinates is presented for analyzing tests of this nature. The practical utility of the equation is demonstrated by practical utility of the equation is demonstrated by analyzing tests involving restricted producing intervals that cannot be treated with existing analytic methods.Practical guidelines for applying the proposed equation are developed by analyzing pressure data generated by a numerical simulator and more complex analytic solutions for variety of special completion situations. Equations for determining static reservoir pressure, formation permeability, and skin factors pressure, formation permeability, and skin factors are derived and their validity verified under theoretical test conditions. The equations presented should have a variety of applications, but are particularly suited for analyzing pressure data from particularly suited for analyzing pressure data from drillstem tests with short flow periods. Introduction The fundamental equation for analyzing pressure buildup tests of oil wells was presented by Horner in 1951. This equation is based on the "line source" solution to the boundary value problem describing the pressure distribution resulting from the cylindrical flow of a slightly compressible fluid in an infinite reservoir. To achieve cylindrical flow the wellbore of a well must completely penetrate the producing formation. Although this restriction is often satisfied, in many tests it is not; for example, oil wells producing through perforated casing may have only a small portion of the total production interval perforated, or in the case of production interval perforated, or in the case of drillstem tests only a small interval (often 10 to 15 ft) of a thick (hundreds of feet) homogeneous formation may be selected for testing. Tests involving restricted producing intervals of this type have a characteristic buildup curve as described by Nisle and by Brons. These authors demonstrated that Horner's conventional equation could also be used for restricted producing interval problems, provided the correct portion of the buildup problems, provided the correct portion of the buildup curve is used. They showed that during a short period after starting production (or equivalently period after starting production (or equivalently after shut-in) the well behaves as if the total sand thickness were equal to the interval open to flow. That is, Horner's equations apply if the total sand thickness, h, is replaced by the producing interval thickness, h. They also showed that after a transition period the late part of the buildup curve could be used in the conventional manner to calculate formation permeability and static reservoir pressure. Kazemi and Seth extended the work of pressure. Kazemi and Seth extended the work of Nisle by including the effect of anisotropy; they also presented an equation, based on an analytic solution developed by Hantush, for estimating the shut-in time required for the development of the second straight-line portion in a conventional plot --i.e., p vs In (t + Deltat/Deltat. The first straight-line part o the buildup curve usually lasts only a few part o the buildup curve usually lasts only a few minutes and may often be obscured by afterflow, whereas the latter straight-line portion may take several hours to develop and may not even occur for practical shut-in times if the formation is thick and the producing time is relatively short. This paper demonstrates that the transition period paper demonstrates that the transition period between the two cylindrical flow periods can be analyzed with the spherical* flow equations presented here. In addition, practical guidelines presented here. In addition, practical guidelines cue developed for their application.Moran and Finklea first suggested that a pressure buildup equation based on spherical now pressure buildup equation based on spherical now was necessary to correctly analyze pressure data obtained from wireline formation testers. In many respects this study is similar; in fact, the basic pressure buildup equation (although it was derived pressure buildup equation (although it was derived from a different starting equation) presented here was used by Moran and Finklea in analyzing wireline formation test data. SPEJ P. 545

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