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Abstract This paper illustrates a detailed workflow to build a compositional simulation model for a large gas-bearing with a sizable oil-rim carbonate reservoir in the Middle East. The workflow is emphasising on the importance of data gathering, validation, analysis and integration in building a sound simulation model from geological and dynamical perspective. One of the main achievements of this work was the concept behind matching the variable producing Gas-to-Oil ratio without jeoporadizing the match of other performance parameters. The key resolution to this problem is the careful setup of equilibration and fluid models.
- Asia > Middle East (0.48)
- Africa > Middle East (0.48)
Abstract Sand screens for specific applications are often selected by reference to the results obtained from laboratory sand retention testing. Some recent publications have highlighted the problems of running some types of sand retention tests (slurry tests) at high flow rates, such that the differences between wire wraps screens and metal mesh screens may be exaggerated. With these in mind and also to address some general concerns of the authors ways to reduce flow rates in laboratory slurry tests to more realistic levels have been investigated. This has created some unforeseen effects which are discussed; video has proved invaluable in understanding these unforeseen effects. In addition, an attempt has been made to better define plugging within sand retention tests by relating the pressure build-up gradient from slurry tests to characteristics of the sand itself. Although the pressure gradient generally correlates to certain sand size and sorting parameters the spread in data suggests another factor is important. The purpose of this work is to try and better define the differences in performance between different screen designs, primarily wire wrap and metal mesh screens, in order to better define their application envelopes in terms of sand quality and hence develop more definitive guidelines for screen selection.
- North America > United States (0.28)
- Europe > Netherlands (0.28)
This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 142996, ’Grid-Based Inversion Methods for Spatial-Feature Identification and Parameter Estimation From Pressure-Transient Tests,’ by K.L. Morton, SPE, and R.J. Booth, Schlumberger; M. Onur, SPE, Istanbul Technical University; and F.J. Kuchuk, SPE, Schlumberger, prepared for the 2011 SPE Europec/EAGE Annual Conference and Exhibition, Vienna, Austria, 23-26 May. The paper has not been peer reviewed. Three grid-based inversion methods for estimating formation parameters and for spatial geological-feature identification based on pressure-transient-test (PTT) data from multiple-well locations were investigated. The first two methods use efficient adjoint schemes to determine the gradient of the objective functions. The third method uses ensemble Kalman filtering (EnKF) for data assimilation. With these methods, the existence and location of many subseismic features, such as strong spatial permeability variations, faults, fractures, and pinchouts, may be determined by use of exploration and production data. Introduction PTTs are used to determine the productivity of a well and the properties of the formation (reservoir) on the basis of downhole and/or surface pressure and flow-rate measurements. The main steps for interpretation are: Model identification—a possible set of reservoir models is found that may fit the data. Model-parameter estimation—model parameters are adjusted until the model behavior matches observed data. Model verification—consistency of the final model is verified by measuring the mismatch between the real system and the model or by comparing with other data. By use of conventional interpretation methods (i.e., semilog methods such as Horner or Miller-Dyes-Hutchinson, and/or type-curve matching of measured pressure and/or pressure derivative), data including reservoir pressure, an effective average permeability of the formation, skin factor, and wellbore storage can be estimated from the PTT data. In such interpretation, some sort of prior modeling is necessary to constrain the nonlinear parameter estimation because a model with many nonphysical reservoir parameters may match the observed PTT data. This prior knowledge may be available at small scale from logs and cores and at a larger scale from seismic surveys and outcrop analogies. Recently, nonlinear least-squares optimization has been applied to PTT data by use of numerical models with a similarly limited number of parameters—often models that are divided into a small number of regions, within which the reservoir parameters are assumed to be constant.
- Europe > Austria > Vienna (0.55)
- Asia > Middle East > Turkey > Istanbul Province > Istanbul (0.25)
This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 146298, ’Automated Alarms for Managing Drilling Pressure and Maintaining Wellbore Stability - New Concepts in While-Drilling Decision Making,’ by Andreas Sadlier, SPE, Chris Wolfe, SPE, Mike Reese, SPE, and Ian Says, SPE, Baker Hughes, prepared for the 2011 SPE Annual Technical Conference and Exhibition, Denver, 30 October-2 November. The paper has not been peer reviewed. With the increased complexity of wells being drilled, significant geologic uncertainty may be encountered during wellbore construction. Uncertainty can take the form of unplanned drilling events such as kicks, lost circulation, and borehole-stability problems. A more proactive effort to predict and identify trouble zones in real time could lead to a substantial reduction in nonproductive time (NPT) and safety risks. Computer systems can automate the filtering and distribution of relevant information to personnel quickly for more-rapid assessment of a situation. Introduction To assess and analyze the current risks, field engineers are tasked with monitoring various measurements and data feeds while drilling and, if potential problems occur, making recommendations for corrective actions. With an increasing volume of more-complex data available in real time, how can engineers analyze relevant information effectively and in a timely manner to mitigate risk? One way is to leverage the power in modern computer systems. Software automates the filtering and distribution of relevant information to personnel quickly for rapid assessment of a current drilling challenge. For example, in a pressure-management (PM) operation, alarms can be activated automatically to provide quick warnings on the basis of equivalent-circulating-density (ECD) measurements (in the context of the mud-weight window) and to indicate potential hazards. These alarms could help filter and interpret complex real-time data sets quickly, without relying solely on the experience of the individual pressure engineer to detect a possible drilling risk. A PM and wellbore-stability (WBS) alarming system was designed to reduce complexity and facilitate PM/WBS decision making in near real time. Background During drilling, the safe-mud-weight window ranges from the pore-pressure gradient (on the low end) to the fracture gradient (on the high end). The goal of real-time PM involves selecting and maintaining the downhole drilling-fluid pressure within the drilling-mud-weight window to reduce drilling NPT (drilling NPT attributed to pore-pressure and wellbore-instability issues is approximately 40%). To reduce this type of NPT effectively, the use of real-time PM engineers is recommended at the rigsite or from a remote monitoring center.
- Well Drilling > Wellbore Design > Wellbore integrity (1.00)
- Well Drilling > Pressure Management (1.00)
- Well Drilling > Drilling Operations (1.00)
- (2 more...)
Technology Today Series articles are general, descriptive representations that summarize the state of the art in an area of technology by describing recent developments for readers who are not specialists in the topics discussed. Written by individuals recognized as experts in the area, these articles provide key references to more definitive work and present specific details only to illustrate the technology. Purpose: to inform the general readership of recent advances in various areas of petroleum engineering. Abstract Pore pressure and wellbore stability pose significant challenges to exploration drilling, particularly in regions featuring weaker rocks or subsalt formations. A lack of accurate pore-pressure prediction and wellbore-stability analysis brings many problems, such as blowouts, kicks, hole washouts, wellbore breakout, and stuck pipe. Wellbore instability also adds to drilling time and increased costs, and sometimes leads to abandoning the well before it reaches its objective. Estimates put the cost of these issues at approximately 10% of total drilling time on average. Ending wellbore-instability problems begins with the ability to predict conditions accurately and to reduce the chance of running into trouble. In this paper, commonly used methods for analyses of pore pressure, in-situ stress, and borehole shear failure are evaluated for their strengths and weaknesses. Examples are provided that demonstrate that the integration of predrill pore-pressure and geomechanics analyses with real-time monitoring consistently provides an effective way to mitigate predrill uncertainties and improve well-construction efficiency.
- Geophysics > Seismic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
We have developed a hyperbolic penalty function for image estimation. The center of a hyperbola is parabolic like that of an norm fitting. Its asymptotes are similar to norm fitting. A transition threshold must be chosen for regression equations of data fitting and another threshold for model regularization. We combined two methods: Newton’s and a variant of conjugate gradient method to solve this problem in a manner we call the hyperbolic conjugate direction (HYCD) method. We tested examples of (1) velocity transform with strong noise (2) migration of aliased data, and (3) blocky interval velocity estimation. For the linear experiments we performed in this study, nonlinearity is introduced by the hyperbolic objective function, but the convexity of the sum of the hyperbolas assures the convergence of gradient methods. Because of the sufficiently reliable performance obtained on the three mainstream geophysical applications, we expect the HYCD solver method to become our default method.
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.51)
- Geophysics > Seismic Surveying > Seismic Processing (0.46)
Marine controlled-source electromagnetic (CSEM) data can be highly sensitive to the presence of resistive hydrocarbon bearing layers in the subsurface. Yet, due to the relatively poor depth resolution of CSEM data and the smoothness constraints imposed by electromagnetic (EM) inversion methods, the resulting resistivity models are often highly smoothed-out, typically underestimating the reservoir resistivity and overestimating its thickness. Conversely, seismic full-waveform inversion (FWI) can accurately recover the depths of seismic velocity changes, yet, is relatively insensitive the presence of hydrocarbons. In spite of their low depth resolution, CSEM data have been shown to be highly sensitive to the resistivity-thickness product of buried resistive layers, suggesting that if the thickness of a target layer can be constrained a priori, very accurate resistivity estimates may be obtained. We developed a method for leveraging the high depth resolution of FWI into a standard CSEM inversion algorithm so that the resulting resistivity models have depth constraints imposed by the seismic structure and consequently may obtain more accurate resistivity estimates. The seismically regularized CSEM inversion that we propose is conceptually similar to minimum-gradient support (MGS) regularization, but it uses regularization weights based on gradients in the seismic velocity model rather than the self-reinforcing model resistivity gradients used in the typical MGS scheme. A suite of synthetic model tests showed how this approach compares with standard smooth and MGS inversions for a range of rock types and hence, levels of correlation between the seismic and resistivity structures, showing that a significantly improved resistivity model can be obtained when the velocity and resistivity profiles are correlated in depth. We also found that this regularization weighting method can be extended to use depth constraints from geophysical data other than seismic velocity models. Tests on a real data example from the Pluto gas field demonstrated how the regularization weights can also be set using a nearby well log, resulting in a more compact estimate of the reservoir resistivity than possible with a standard smooth inversion.
- Oceania > Australia > Western Australia > Burrup Peninsula > North West Shelf > Carnarvon Basin > PL WA-350-P > Pluto Field (0.99)
- Oceania > Australia > Western Australia > Burrup Peninsula > North West Shelf > Carnarvon Basin > PL WA 34-L > Pluto Field (0.99)