- Home
- Conferences
- Conference Proceedings
- Conferences
First EAGE Integrated Reservoir Modelling Conference - Are we doing it right?
- Conference date: 18 Nov 2012 - 21 Nov 2012
- Location: Dubai, United Arab Emirates
- ISBN: 978-94-6282-069-2
- Published: 25 November 2012
47 results
-
-
Lithology/fluid Prediction from AVO Seismic Data
By K.H. OmreSeismic 3D AVO data from the Alfheim field in the North Sea are inverted into lithology/fluid classes, elastic properties and porosity. The maps provide more reliable estimates of the hydrocarbon volumes in the field. The inversion is phrased in a Bayesian setting. The likelihood model contains a convolutional, linearized seismic model and a rock physics model. It also contain several global parameters that are estimated from seismic and well observations. The prior model on the lithology/fluid classes is a Markov random field that captures local horizontal continuity and vertical sorting of fluids due to gravitation. The predictions from the posterior model are verified by the use of five blind wells. Hydrocarbon volumes with reliable gas/oil distributions are predicted. The presentation will focus on the use of spatial statistics in lithology/fluid prediction and demonstrate the improvements made if reliable modelling is done. Validation of the predictions on observations in five blind wells make the results conclusive.
-
-
-
Reservoir Modelling Conditioned by Seismic Data Using Sequential Gaussian Mixture Simulation
By D. GranaReservoir models integrating seismic data are generally obtained as a solution of a complex inverse problem involving geophysical models and geostatistical methods. We propose here a new methodology to obtain high-detailed reservoir models in terms of facies and rock properties as a solution of a linearized inverse problem given well log and seismic data. This methodology overcomes the assumption of Gaussian distribution of reservoir properties by using Gaussian mixture models to describe the multimodal behaviour of the data. In this method we combine geostatistics and linear inverse theory to sample from the posterior distribution of a Gaussian mixture linear inverse problem to obtain multiple realizations of reservoir properties characterized by multimodal behaviour.
-
-
-
Integrating Petro-elastic Seismic Inversion and Static Model Building
More LessThis presentation focuses on various aspects of how the results from stochastic, petro-elastic seismic inversions can be used in 3D static models. Scale issues can be handled in the inversion, in a downscaling step, or by working on a single scale. For an update to be consistent in both time and depth, the inversion should also do geologically meaningful structural updates. The uncertainty estimates provided by the stochastic inversion should drive the amount of variability in the static model(s).
-
-
-
Integrating Stochastic Seismic Inversion into Reservoir Characterisation Workflows
Authors R. Moyen, R. Porjesz and A. BouziatSeismic inversion is a widely used technique, but it is difficult to quantitatively integrate its results in geological or reservoir models. This is in part due to the difference of scales, and to the difficulty in properly modelling the petro-elastic relationships. We propose to use stochastic seismic inversion, that computes a large number of fine scale models at a scale closer to the geomodel, to quantitatively estimate the uncertainty associated to the inversion process. We then expose how the results from stochastic inversion can be integrated into geomodels, to compute a seismic-driven facies model that accounts for uncertainties. It is also possible to compute porosity models guided by the wells and the seismic, illustrating the value that seismic can bring even when the well density is high.
-
-
-
Inversion of Dynamic Properties from 4D Seismic, Ensuring Coherency between Geology, Engineering and Rock Physics.
Authors T.D. Blanchard and P. ThoreWe showcase a method to provide 4D seismic information in the reservoir engineering domain, making integration into AHM loops more straightforward whilst ensuring that the 4D signal, production data and geology are coherent at the well through calibration of the poro-elastic model. An example is shown on a field undergoing production and water injection.
-
-
-
Seismic Inversion in a Geological Bayesian Framework
More LessReservoir characterisation is invariably a data integration exercise; no one type of data provides enough information on its own. Therefore it must also be a multidisciplinary process which, ideally, should be inclusive and transparent allowing each discipline to be able to understand and control their contribution and adjust it as new data and new insights become available. Effective integration requires estimates of the uncertainties of each data type in order to control the relative weighting of their respective contributions. Bayesian methods provide a framework for this and several seismic inversion strategies utilising Bayesian methods have been proposed. They typically set up the Bayesian scheme in a geophysical framework such that the integration occurs near the beginning of the process. An alternative proposed here is a Bayesian scheme framed in a geological domain with priors and likelihoods defined directly in terms of reservoir parameters. This requires that reservoir properties and associated uncertainties are estimated, as far as possible, independently from each data type and are then combined towards the end of the process. The talk will outline the process and provide some illustrations.
-
-
-
Lies, Damned Lies and a Grain of Truth
By C. DalyModeling of reservoirs has become more mathematically sophisticated over the last twenty years. In particular stochastic models have become the norm in very many, if not most reservoir studies. The reasons for this are threefold 1) The advance of stochastic reservoir modeling as a science exposed the shortcomings implicit in the older deterministic models, namely underestimation of the role of heterogeneity. 2) Stochastic methods provide the best mechanism to incorporate various data types into a model. 3) They allow for some understanding and modeling of the uncertainty present in the reservoir. We have arrived at a point in time where many of the standard techniques for modelling are available in all of the principal commercial software packages (which is not to say that the methods cannot and should not be improved further). It may therefore be a good time to ask the wider question about how they are being used in practice particularly with regard to the major issue of understanding risk. In this presentation we look at how closed mathematical models, while being a fundamental building block, do not lead, on their own, to a good methodology for understanding risk. An analogy with the mathematisation of risk in banking and the credit markets is noted. The conclusion, which is very obvious, is to increase the amount of speculative geological model building and peer to peer discussion about scenarios. However, the current practice of reservoir modeling provides stumbling blocks making users reluctant, or even unable to easily explore differing scenarios. Indeed this difficulty extends beyond heterogeneity modeling into geophysics, petrophysics etc. To change this is a big task, which we don’t pretend to have resolved here, but by shining light on the problem, and by making a small suggestion to improve matters for heterogeneity modeling, we hope to open discussion about the subject.
-
-
-
Recent Developments in the Use of Outcrop Analogues for Building Better Models of Subsurface Reservoirs
By J. HowellSparsity of data remains a significant challenge to the effective modelling of subsurface reservoirs. Measurements of the reservoir are limited to wells, which provide high quality 1D data but are typically spaced hundreds to thousands of metres apart and seismic data, which provide 3D coverage but the resolution is typically below the scale of individual architectural elements that control fluid flow. Outcrops that are analogous to the depositional systems within an oil field provide one means of collecting geological data that can be used to populate geologically realistic reservoir models. There is a long history of study within this area however two challenges exist: 1) the acquisition of sufficient, quantitative data that are suitable for use in reservoir modelling and, 2) matching appropriate analogues to specific subsurface problems. These problems are being addresses through recent advances in outcrop data acquisition, processing, storage and application are revolutionizing the use of analogues in the oil industry.
-
-
-
A New Approach for Making Identical 3D Training Images of Complex Geological Analogues
Authors M V. Thachaparambil, Z. Zhu, Q. Liu and T. ZhangA new approach for making identical 3D Training Images (TI) for multipoint statistics (MPS) and object based reservoir models of complex geological analogues is presented. It bridges the current gap in bringing complex facies assemblages quickly into a reservoir model without losing the essential geometric shapes and geological associations. It also provides an opportunity to validate the analogue selection. Ultimately this method allows geologist to transfer outcrop data and conceptual models directly and effectively into reservoir grids, and to efficiently form geologically relevant complex reservoir facies models.
-
-
-
Integrated Reservoir Modeling and Simulation with Unstructured Grids
Authors X.-H. Wu and L.V. BranetsIn this talk, we present a new integrated approach to reservoir modeling and simulation by using unstructured grids and other novel modeling techniques. We give brief review of the application of unstructured grids and why existing modeling techniques can hinder the effective use of unstructured grids. New modeling approaches based on hierarchical functional form representation and novel unstructured gridding techniques developed to facilitate the creation of unified geologic and simulation models are presented.
-
-
-
-
A Fast and Consistent Geostatistical Approach for Constraining 3D Structural Models to Horizontal Wells
Authors P. Abrahamsen, P. Dahle and A. SkorstadThe use of horizontal well data in 3D reservoir modeling has become an increasingly important task as the use of horizontal wells has become common practice. Standard gridding approaches are based on the use of well picks to define the positions of stratigraphic surfaces along well bores. Horizontal wells however, are often drilled almost parallel to the stratigraphic layering so the number of horizons intersected along a horizontal well can be relatively few. Therefore, horizontal sections of the well can be used to constrain the structural position of reservoir zones. A robust, geostatistical approach has been developed to ensure consistent use of horizontal well data in the construction of 3D structural models. Kriging is used for prediction of surface location based on well picks and constraints obtained from zone logs along horizontal wells. In contrast to standard approaches, all well data (picks and constraints) from all surfaces are treated simultaneously and will have impact on all surfaces above and below. The geostatistical approach is fast and reproducible, and allows structural models to be updated continuously as new wells are drilled. The uncertainty can be evaluated by kriging error maps or by generating stochastic realizations that honor all the well data.
-
-
-
Building High Resolution Microblock-models to Model Upscaling Behaviour of Heterogenous Carbonates
Authors M.P. Suess, M. Bartenbach, T. Aigner and M. BaumhoerProper sampling of plugs and upscaling are key steps in generating reservoir models. At core scale many carbonate reservoir rocks exhibit extreme variations in permeability which can frequently not be captured by conventional core plugging. Whole core studies, which investigate the dynamic behaviour at core scale are costly and time extensive. We present a set of 3D microblock models at decimeter scale, which aim to represent the full heterogeneity of carbonate reservoir rocks. The textures range from highly irregular algal mudstones through clast supported wacke- packstones to bioturbated mudstones. The structure of the depositional sedimentary elements at this resolution were mapped in cores and translated into the micromodels using various geostatistic techniques. In example multipoint geostatistics was used to model complex shapes like floating coral debris. Permeability was measured every centimeter using a minipermeameter. The core material was then plugged at centimeter scale and porosity was measured at the generated mini-plugs. The properties were mapped, geostatistically evaluated and simulated using a 3D modeling package. Applying conventional flow simulators in lab mode we study the two-phase flow behaviour of the modeled reservoir rocks and compare to analytical upscaling predictions. We can show how flow is dominated by high permeability streaks at core scale and can simulate under which conditions such behaviour is preserved at reservoir cell scale.
-
-
-
Integrated Reservoir Modelling Assurance Workflow
By A. MiottoThis paper proposes an Integrated Reservoir Modelling (IRM) assurance workflow based on three simple steps: check, review and assure. This method is necessary to guarantee consistency between input data, full field model and results which make geological, petrophysical and reservoir engineering sense.
-
-
-
Light-UP, an innovative approach to uncertainty evaluation and communication
Authors E. Tawile, P. Schirmer, F. Duclos, T. Hu and S. AhnLight-UP (for Light Uncertainty Process) is the reference TOTAL in-house tool for uncertainties management. Light-UP provides (1) the assessment of the probabilized HIIP distribution thanks to the quantification of uncertainties around the Base Case model and (2) the methodology and tools to build “tailor-made” models that drive fluid flow simulation for reserves evaluation with or without dynamic uncertainties.
-
-
-
Gigapixel Photographic Technology for Integrated Reservoir Characterization: A Deepwater-Reservoir Outcrop Example
Authors M.K. Czernuszenko, O.J. Varela and C.S. CalvertDetailed characterization of outcrop analogs can provide useful insights for understanding the reservoir geology and for constructing realistic reservoir models. Outcrop data can provide information about reservoir facies and properties, small features not imaged by seismic data (e.g., thin beds, thief zones, fractures), and spatial variability (continuity) and statistical distribution of key properties/features. Gigapixel technology allows the above information to be extracted in an easy manner. Digital photopans can be zoomed in and out to identify, for example, the extension of shale beds or structural faults. This paper will present a description of the technology and how it is integrated into existing subsurface workflows using a deepwater example. We have developed workflows that allow for the integration of observations made in the field with those interpreted on gigapixel panoramas. Measured sections, microscope images, facies descriptions and other observations are directly referenced on the photopan and used for characterizing geology, understanding well data, and for constructing reservoir models. We have been applying these workflows in the past few years and they have made impact in each one of the applications described above, in particular for the characterization of reservoir facies and properties.
-
-
-
Reservoir Performance Forecasting – How Well Are We Really Doing?
Authors W.S. Meddaugh and N. ChampenoyReservoir forecasts tend to be optimistic. Forecasts for IOR/EOR projects tend to be particularly optimistic. Sources of the optimism can be divided into several broad categories including: Data – quantity, quality, sampling bias; Static Modeling – model complexity, particularly for permeability contrasts; Model parameter/algorithms choice; and, Dynamic Modeling – model detail/complexity, up-scaling, well location optimization. In addition, human factors also tend to drive projects towards optimistic forecasts. Based studies of a number of reservoirs representing a variety of lithology types and depositional environments with data densities ranging from low (greenfield) to extremely high (multi-pattern pilots) observations on modeling and forecast accuracy can be made relative to IOR/EOR forecast results, in particular. Among the most critical modeling parameters are the areal grid size and the semivariogram range parameter. Optimistic estimates of the in place hydrocarbon volume is also one of the most significant sources of optimistic forecasts. Some of this latter bias is due to sampling, particularly for green-field developments, and some due to inappropriate use of analogs. This bias can be reduced with uncertainty-based analyses and workflows and an appropriate suite of analogs. Well location optimization based on stochastic models is an under-appreciated source of forecast optimism.
-
-
-
Estimating the Cloud Transform
Authors O. Kolbjornsen, A. MacDonald, A. Skorstad and T. BergWe present a new method for estimation of the cloud transform. The cloud transform is used for modelling complex dependencies when co-simulating reservoir variables. We compare the proposed approach to two standard approaches for two data sets and find that the proposed approach gives improved properties of the resulting transform.
-
-
-
Geomechanics, Faults and Fractures Modelling
More LessIn recent years, the petroleum industry achieved marked advances in the development of full 3D geomechanical models (both static as well as dynamic). If robust, these 3D models provide the benefit for more accurate well and field development planning in structurally complex settings such as areas with significant topography or/and faulting, or/and when substantial pore pressure changes in response to injection or/and depletion are likely to cause changes in the in situ stress field. These stress changes may then be accompanied by phenomena such as fault and fracture reactivation, reservoir compaction and surface subsidence etc. Furthermore, proper 3D geomechanical modeling is often required when wells are planned to intersect salt diapirs or other frictionless bodies/layers with different material characteristics. In many cases, these 3D geomechanical models also require advanced finite element modeling coupled with reservoir simulation. To maximize the value from such modeling, in particular understanding the in situ stresses, pore pressure, and material properties and their variability (lateral, in depth as well as with time) are of critical importance to better evaluate and mitigate risk during the drilling, completion, and production phase of a field development. In other words, a sound and accurate 3D structural model is critically important, since it not only covers the structural elements and layering (stratigraphy) of the reservoir but also the overburden all the way to the surface (or seafloor in offshore environments); it thereby provides the basis for a 3D geomechanical model. When combined with a well calibrated fracture network model (e.g., DFN), 3D geomechanical models can be utilized to investigate the possibility for natural fractures to be or become critically-stressed in response to production or injection and evaluate the impact on the reservoir-wide permeability tensor as a function of time. This presentation will provide an overview of the basics of 3D static as well as dynamic geomechanics and how it is linked and integrated with structural modeling, discrete fracture network models as well reservoir simulation. Current model limitations and a future outlook as to where technology develop is and should head is also included in the discussion.
-
-
-
Integrated Workflow and the Application of a Fully Coupled Geomechanical Flow Simulator for Shales
Authors M.A.C. Kemper, S.J. Emsley and E. ZahedStudies dealing with the elastic properties and seismic response of shale reservoirs are relatively few. Mapping the distribution of sweet spots and identifying their thermal maturity, organic carbon richness and natural fracture network using seismic data are considered to be of importance for the exploration and development of shales. These studies can be developed to include the analysis of fracture information from seismic data and VSP data all of which form inputs to a fully coupled geomechanical flow simulator which can be used to forward model fluid flow and accurate displacements and stresses at any location and time. Combining these with the microseismic data both forward modeling and measurement and analysis allows for the generation of a calibrated coupled geomechanical flow simulator to predict to predict drainage areas, production rates and ultimate recovery.
-
-
-
Seismic to Simulation Modeling of a Green Middle Eastern Naturally Fractured Reservoir
Authors M.M. Faskhoodi, D. Astratti, L. Souche and P. MenegattiThis Middle East case study addresses the modelling of a Type 2 (Nelson, 2001) green carbonate reservoir which production is acknowledged to be largely controlled by fractures. In the case of an undeveloped reservoir the main challenge is posed by the limited amount of hard data and production history. The ultimate objective was to minimize production forecast uncertainties. This was achieved by means of a workflow that integrates 3D seismic, well and production data.
-
-
-
Hydraulic Fracture Stimulation via Coupled Reservoir Geomechanics – The Nikanassin Unconventional Formation in Canada
Authors Gaisoni Nasreldin, L. Gonzalez, J. Rivero, P. Welsh, R. Aguilera and N. KoutsabeloulisThis paper presents an integrated 3D workflow for multi-stage hydraulic fracture stimulation by embracing 3D geomechanics, with a view to help unlocking these reserves. In the proposed approach the geometry and orientation of the multiple hydraulic fractures are driven by the prevailing 3D stress state in the drainage zone in the vicinity of the stimulated well. A case study involving two-way geomechanical coupling approaches is used to carry out a Class C1 “prediction” of the performance of a horizontal well drilled in the Nikanassin naturally fractured tight gas formation (Western Canada Sedimentary Basin). The results of the computations demonstrate the benefits of including 3D geomechanics in dual porosity flow simulations, particularly in connection with closely matching the gas production history. Moreover, the ability of the method to estimate the unavoidable reduction in permeability of natural and hydraulic fractures associated with pressure depletion leads to more realistic production predictions when compared with cases when ignoring geomechanical effects. The telling conclusion is that the field of hydraulic fracture stimulation provides an object lesson in the need for coupled 3D geomechanical approaches. The method presented in this paper will help improve gas rates and recoveries from low-permeability reservoirs.
-
-
-
Assimilation of Dynamic Data: Are We Doing it Right?
By D.S. OliverIn this talk, I will review the history matching problem for petroleum reservoirs, emphasizing progress and limitations, beginning with a discussion of the purpose of history matching. Because the data are typically quite limited, I will emphasize the ability to quantify uncertainty in reservoir predictions and the importance of the choice of model parameterization on the ability to match data and to assess uncertainty. Particular problems associated with updating of complex reservoir models will be identified. Although the focus of the talk will not be on methodology, I will discuss the consequences of various choices of methodology on parameterization and the limitations of various methodologies. Finally, the Norne Full-Field case will be used to illustrate many of the history matching concepts discussed earlier. This field is highly faulted, contains vertical flow barriers of unknown continuity, has multiple initial oil-water contacts and gas-oil contacts. Water and gas have both been injected at various times. Production data, including RFT and phase production and injection rates have been measured in a relatively large number of horizontal and vertical wells and 3D seismic surveys have been repeated periodically. Identifying model parameters with sufficient flexibility to match all of the data is a challenge.
-
-
-
History Matching: Towards Geologically Reasonable Models
Authors Y. Melnikova, K.S. Cordua and K. MosegaardThis work focuses on the development of a new method for history matching problem that through a deterministic search finds a geologically feasible solution. Complex geology is taken into account evaluating multiple point statistics from earth model prototypes - training images. Further a function that measures similarity between statistics of a training image and statistics of any smooth model is introduced and its analytical gradient is computed. This allows us to apply any gradient-based method to history matching problem and guide a solution until it satisfies both production data and complexity of a prior model with desired accuracy. As a consequence of the approach, we sufficiently decrease the amount of forward simulations needed to resolve historical data and prior information.
-
-
-
Novel Metric Space Methods for Data Integration
Authors D. Fenwick and J. CaersIn mathematics, a metric space is a set where a distance (called a metric) is defined between elements of the set. Metric space methods have been employed for decades in various applications, for example in internet search engines, image classification, or protein classification. In petroleum reservoir modelling however, metric space methods are not widely known. In this paper, we introduce the concept of a metric space in the framework of reservoir modelling. The metric space is formed by calculating a distance between two models. The distance is analogous to the well-known concept of an objective function in optimization, with the exception that the distance is not only evaluated between the model response and historical data, but also between two reservoir model responses. We describe how placing an ensemble of reservoir models in metric space allows for novel methods for visualization and analysis of model ensembles, reservoir uncertainty, and data integration.
-
-
-
Dynamic Validation of a Multi-Point Statistics Model using Extended Well Test Data
Authors P. Bergey, P.J. Ruelland and H. HamdiIn Field A, an extended well test carried out over 5 months was used to validate 5 facies models generated with Multi-Point Statistics, each declined into a set of petrophysical models. The geological context of Field A is that of low NTG fluvial deposits which include channel and bar sandstones, alluvial splay siltstones and flood plain shales. Sparse static conditioning data, limited spatial information and naturally complex 3-D channel networks imply that various models can be equi-probable. Multipoint statistics (MPS) approaches were used to model sedimentary bodies in order to ensure the consistency between the model and the geological understanding. Simulation of the conditioned MPS models enabled to reproduce a set of extended well test responses and hence compare the dynamic behaviour of the models against that of the reservoir. Successive comparisons enabled to extract 2 MPS models which matched respectively the early and late time well test data. To obtain a better match over the whole well test data, an engineering-based hybridisation algorithm was used to combine the 2 better-fit models. The successful implementation of this algorithm resulted in promising results and enabled to obtain a quality match with the real well test data.
-
-
-
Parameterization in History Matching: State of the Art and Perspectives
Authors M. Le Ravalec-Dupin and F. RoggeroHistory matching consists in estimating spatially variable petrophysical parameters among which facies, porosity or permeability. These parameters, which are keys to understanding fluid flows, are difficult to measure. However, they can be inferred from measurements of related variables such as flow rates, pressures, gas oil ratios... This is actually an inverse problem, which is intrinsically "ill-posed". This concern motivated the development of many techniques to solve history matching. They differ most significantly in their approaches to parameterization. Parameterization deserves special consideration because it strongly influences the "well-posedness" of the inverse problem and the physical validity of its solution. A suitable parameterization technique makes it possible to reduce the number of parameters, but also to preserve the spatial variability of the inverted properties. Otherwise, the inverted models lack geological realism. We propose to review the main parameterization techniques and distinguish two main families: those, which adopt either a blocked or a geostatistical description of spatial variability. Briefly, the first approach splits the reservoir into a number of discrete blocks characterized by uniform petrophysical properties. These ones are then considered as parameters to adjust in order to match the available production data. The geostatistical alternative views the properties of interest as stationary random fields. In this case, various methods have been proposed to vary realizations of random fields to fit the production data while still respecting the prior spatial variability captured either by two- or multi-point statistics. Referring to the multiscale nature of rocks, we suggest to merge the two main parameterization groups mentioned above, thus resulting in a multiscale parameterization approach. The technique envisioned is based upon sequential simulation and provides the ability to vary both continuous and discrete petrophysical properties at the block scale or at a finer scale while preserving a consistent link between the scales.
-
-
-
Risk and Uncertainty in EP - Where Are We?
By T. NguyenUncertainty analysis and modelling in EP evaluation is one of the main focus for the oil industry during the last decade and many progress have been made on the subject, although there are still more improvements to come as the problem is far from being trivial. This key note talk will share with the audience the state of the art we are today with different uncertainty analysis and modelling techniques used by the industry in order to identify and reduce potential risks involved. Uncertainty analysis is the first and crucial step, aiming at identifying correctly the key uncertainties, their related nature (bias or variance errors) and their impact on the results under consideration. Weak signals from measurements should be scrutinized and analogues should be investigated in case of sparse data or information. Uncertainty modelling is the final step using either well known deterministic approach or more complex probabilistic ones. The process is closely linked with the geological and reservoir modelling tasks and must comply with the objective which has been set up beforehand. Their applications and limits are frequently subject of debate, as well as the long time it took to complete the whole process, sometimes with hundreds of models to be generated and investigated. At the end, the communication of the uncertainty results to different parties is not always an easy task, since the probabilistic language is seldom popular among operational staff and especially when the operational needs differ greatly from one group to another. Big challenges still lay ahead for a more comprehensive approach for uncertainty analysis and modelling with a trend towards larger models of the subsurface and more realistic representation of reservoir heterogeneities. However, mastering the uncertainties and risks is the sole way for a better exploration and development.
-
-
-
Uncertainty Quantification: Are We Doing it Right?
By M BeardsellThere is no more easy oil! This means when we find hydrocarbons today it is a risky business …. small reservoirs, tight reservoirs, deep reservoirs etc. It is therefore more important than ever to quantify the risk associated with each prospect. Practically this means evaluating the uncertainty in our reservoir models. For more than a decade now software vendors have been providing tools to aid in the evaluation of uncertainty. With time these tools have become easier to use and cover a broader range of the modeling process. Despite this, uncertainty quantification has had limited adoption across the industry and tends to lie in the hands of a few experts. There is a shortage of best practice procedures and we can be sure that many mistakes are being made. This presentation will start by laying out the principal workflows and open up for discussion important questions such as: How do we decide which of the multitude of parameters we should focus on? How do we combine scenarios with realizations? What strategies are available to link the static uncertainty with the dynamic? How can Uncertainty play a role in history matching and prediction? What is the role of optimization?
-
-
-
Realities and Expectations of Reservoir Modelling
More LessReservoir modelling both static and dynamic has advanced drastically with the advancement in computing and visualization technologies. However, the accuracy and the effectiveness of reservoir modelling rely on a number of factors that goes into the modelling processes and the data that is used to construct those models. The idea that a model will be solid representation of the reservoir in question has to be qualified carefully and the notion that one can build a perfect model has to be questioned. In my presentation I will touch on some of the factors that impact model results and show actual examples.
-
-
-
Mapping The Distribution of Gas Hydrates Using Coloured Inversion and Rock Physics Modeling in Blake Ridges, USA
More LessGas hydrate is important to learn because it related to the stability of the seafloor that can lead to a blowout at an offshore drilling, but other than that can also be used for natural gas resources. The data used in this study is public domain seismic data in the form of PSTM 3D data from the Blake Ridge offshore, South Carolina,USA. Several studies in the Blake Ridge offshore concluded that this area is showing signs of the existence of gas hydrates. In this process, rock physics modeling and fluid substitution analysis is required to provide a picture of the behavior of the elastic parameters of the existence of gas hydrates and gas hydrate relationship with the matrix and other fluids in the rocks. Fluid substitution modeling results, the existence of gas hydrates lead to higher acoustic impedance that is expected to perform post-stack inversion estimates of hydrate distribution can be made. Mapping the distribution of gas hydrates can be done using coloured inversion techniques on 3D seismic data. Coloured Inversion can provide a picture of the relative impedance using the local velocity trend,gas hydrates represented by the most positive relative acoustic impedance.
-
-
-
Improving Reservoir Characterization Using a Qualitative Analysis From Seismic Data. Orinoco Heavy Oil Belt, Venezuela
Authors L. Velasquez and J. CarreñoThe results of a structural and stratigraphic interpretation using seismic data of the area between Morichal and Cerro Negro Fields in The Orinoco Heavy Oil Belt in Venezuela are discussed. The seismic reflections at the top of the target interval (The Terciary Morichal Member of the Oficina Formation), have good continuity and reflection character, however, the challenge is to understand the reflection character at the center and in the bottom of the massive sands that comprise this reservoir, where the acoustic impedance contrast becomes poorer in a paleo-environments that suggest a high-energy of sedimentation. The methodology involves definition of regional markers integrating cores well logs and seismic data. To achieve the objective of the study, it has been fundamental the extraction of stratal slices from volumes derived from multi-attribute analysis and facies classification within target interval. These representative stratal slices and facies results for each unit have been correlated with sedimentological analysis, net sand maps and available production tests, constraining stochastic simulations (SIS) of properties for calculations of OOIP volumes for the area. Finally, feasibility study for seismic inversion performed in this study demonstrated that elastic parameters are the best choice to perform a quantitative seismic characterization for the area.
-
-
-
Charactrization of Spatial Lithofacies Continuity of Arab-D Reservoir Using Modeled Semivariograms: Outcrop Approch
Authors H. Eltom, M. Makkawi and O. AbdulatifThere are strong links between semivariograms parameters and the geological variables of the Arab-D reservoir outcrop analogue, Central Saudi Arabia. Facies analysis of the outcrop revealed seven lithofacies including: platy mudstone, dolomitic mudstone, dolomitic wackestone, stromatoporoid wackestone and packstone, peloidal sandy grainstone, laminated fossiliferous sandy grainstone, and breccia. Indicator semivariograms for these lithofacies were constructed in different directions using lithofacies logs from the outcrop to determine the direction with the best spatial continuity. North-South direction has the best continuity for most of the lithofacies. Laminated platy mudstone, stromatoporoid wackestone and packstone, dolomitic mudstone and dolomitic wackestone show good semivariogram shape, while semivariogram for peloidal sandy grainstone, laminated fossiliferous sandy grainstone and breccia only loosely fits the data in both the major and minor directions. The differences in semivariograms parameters were attributed to variation of the geological variables which include vertical layering of the outcrop, lateral facies changes, and topographical control of the outcrop. The study of outcrop semivariograms allows for visualization of lateral and vertical lithofacies variation in a higher resolution than that of the oilfield scale. This study indicates that outcrop base semivariograms have a significant implication on subsurface reservoir characterization.
-
-
-
DelineatingThickness Distribution Based on Snesim Simulation
Authors C. Pardosi, D. Hapsari, S. Winardhi and A. SyahputraThis Paper presents an approach in estimating sand distribution in a fluvial environment by using gradient of spectral decomposition as the soft constraint data. Training image used in the simulation is fluvial model with certain pattern and probability of sand and shale. As soft constraint, spectral decomposition is used to identify the thickness of sand within the area, and also to determine shale area. Then validators are used to analyze the reliability of MPS.
-
-
-
Permeability and SW Modeling In Carbonate Reservoirs Using Cloud Transform
Authors M. Essam and A. Ghani GueddoudThe Cloud transform reproduces the conditional distributions of a dependent 3D parameter given an independent 3D parameter (Bashore et al. 1994). This distribution is estimated empirically from well data and the secondary variable. The estimated distribution will then be the basis for the cloud transform. This works in the same way as the Normal score transform except that the CDF being used is a 2D CDF estimated empirically from well data and the independent 3D parameter. This allows specifying a model that reproduces the scatter plot from the wells in a 3D volume. In a case study from offshore Abu Dhabi, the relationship between porosity and permeability is found to be non-linear and Cloud transform technique was applied for permeability distribution. The porosity, which is populated using Gaussian Simulation used as independent 3D parameter and an empirical relationship was derived between porosity (3D parameter) and log derived permeability (calibrated to core at well location for each rock type, which was used to estimate permeability distribution for the Cloud transform. The initial simulation results show positive results where good history match was reached without applying multiplier for the producing wells.
-
-
-
-
Carbonate Rock Types Matrix, the Initial Rock Properties Classification Catalogue
Authors O. Al-Farisi, H. Belhaj, S. Ghedan, S. Negahban and J. GomesIn carbonate, the rock typing work that’s been performed during the last two decades had a little progress in term of providing reliable estimation of reservoir behavior. However, lately in 2009, the development of Conjunction Rock Properties Convergence, CROPC, a carbonate rock typing concept that provided an important and easy solution to the carbonate rock typing gaps has a major breakthrough. the need to identify more complex carbonate pore network had led to the initiation of developing the Carbonate Rock Type Matrix CaRTM, which will be detailed in this paper, as part of a Master of Science research project. In this novel concept the carbonate rocks were classified into homogeneous, single pore network, and heterogeneous rocks, dual and triple pore network with the utilization of the effective petrophysical properties of permeability, capillary pressure, saturation, porosity and height above free water level , all were classified in a conjunction matrix that honors these properties and at the same time enables generating sub groups as down scaling and estimation for unseen groups with infinite rock complexity capturing, at the same time it enables the ease to lump the groups and generates upscaled groups that make it easier for utilization.
-
-
-
Integrated Reservoir Geomechanics for Heavy Oil SAGD Design
Authors N.L. Deisman, R.J. Chalaturnyk, M.M. Khajeh, S.O. Ojagbohu and M.H. HamoudThe U of A recent work has been aimed at key components and uncertainties around the safe design of Steam Assisted Gravity Drainage for shallow heavy oil production. It has been demonstrated that during SAGD process, geomechanical behaviours heavily influence both the production of oil, and the integrity of the reservoir system. This work highlights the recent work through an integrated SAGD example. It is common practice to deploy geostatistical approaches to create several fine scale reservoir realizations and then upscale. However, geomechanically, these realizations are not included. As well, during production, permeability and porosity are geomechanically influenced during recovery however it is assumed that the relative permeability is unchanged. Several approaches have been deployed to assess the factor of safety for the reservoir caprock however, classic geotechnical approaches have not been used. This work will demonstrate through a synthetic project, an approach to upscale geomechanical properties from fine scale geostatistical realizations. Next, laboratory data will be shown on how relative permeability changes due to geomechanical influences during production. This data will then incorporated into coupled reservoir geomechanical simulation for several scenarios. Lastly, caprock integrity will be examined using a technique adopted from classic geotechnical engineering for slope stability problems.
-
-
-
Enforcing Geological Consistency Through Interactive Seismic Flattening While Interpreting
Authors S. Panhaleux, M. Palomas, E. Malvesin, T. Laverne and L. SoucheBuilding a geologically consistent interpretation of a structurally complex area (thrust belts, flower-structures, etc.) is often a challenge, especially when the structure has to be interpreted from sparse data (e.g., 2D seismic lines) or when the quality of the seismic image is poor. A solution to these problems is to perform detailed interpretation in a domain in which the considered seismic section has been unfaulted and unfolded in a mechanically consistent way, without breaking the immersive experience of seismic interpreters. In this paper we present a software tool which performs a fully automated flattening process, which is tolerant to minor flaws in the input interpretation, able to handle the most complex structures (X, Y, λ, and thrust fault patterns), and integrated into a seismic interpretation platform. Two user workflows are proposed: (1) a QC of the structural and stratigraphic consistency of an already interpreted seismic section, and (2) an easy tracking of reflectors across faults, by interactively interpreting seismic horizons into a mechanically-flattened section, from which most tectonic deformation has been removed.
-
-
-
Improve Convergence Rate of Seismic History Matching using NAPG
Authors S. Arwini and K.D. StephenHistory matching is a very important activity during the development and management of petroleum reservoirs. Matched models are fundamental to ensure reliable future forecasts, and enhance the level of understanding of the field via geological and reservoir models. Automated history matching (Figure 1) uses a mathematical algorithm to help choose new parameter values so that models better match historical data. The algorithm may be deterministic such as a gradient based method or stochastic such as a genetic or neighbourhood algorithm (NA). The former finds optimal solutions rapidly but the overall search is limited. Locally optimum solutions are all that may be found and uncertainty analysis is not effective. Stochastic methods are quasi-global but can be quite expensive. In this work we consider an approach to speed up the convergence rate of the NA. A proxy model is used to direct the stochastic search using gradients more effectively than is usual for the NA (Arwini and Stephen 2010). We call the new method Neighbourhood Algorithm with Proxy derived Gradients (NAPG). This results in finding solutions with far fewer models. The approach is further improved by updating the proxy model as we progress with history matching and the initialization is optimized using experimental design methods. We apply the approach to the Schiehallion field where we also use time lapse (4D) seismic data as dynamic constraints to reduce uncertainty to get a more reliable model that we might use it afterwards for the forecasting.
-
-
-
Time Depth Conversion and Bulk Volume Uncertainty Estimation of a Prospect using well and Seismic Velocity Data
Authors L. Schulte, B.H. Tan and G.C. TayThe bulk volume uncertainty of an oil & gas field, offshore peninsular Malaysia is estimated from the depth error analysis of the depth converted structure. The study area is covered by 3D seismic that delivered the seismic velocity cube (RMO velocities). Eleven wells with check shot surveys were available for the seismic velocity calibration and the depth uncertainty estimation. The depth prediction and depth uncertainty estimation of the reservoir were checked against new wells that are being drilled during the year 2012.
-
-
-
Gas Hydrate Reservoir Modeling and Validation
Authors E.G. Gloaguen, C.D.B. Dubreuil-Boisclair, B.G. Giroux and D.M. MarcotteThe decrease in conventional gas reservoir new discoveries combined with the increase of the market and improvement of the exploitation technologies push the industry to look for unconventional gas resources. Gas hydrates are one of the largest unconventional resource but also one of the less known. In this study, we use a modified bayesian algorithm in order to simulated gas hydrate grades at Mallik, TNO, Canada constrained by 3D seismic acoustic impedances. The results are validated using a high resolution seismic tomographic inversion. Even with the poor quality 3D seismic data, the proposed method is found to be very robust to estimate gas hydrate grades at Mallik.
-
-
-
Practical Challenges & Recommended Solutions
More LessThis research shows the experience gained from characterizing and modeling 31 oil and gas fields located within the Middle East and North Africa regions. Analyzing and interpreting the results of these studies showed that five factors are affecting to a great extent the field development scenario(s). Regardless of the reservoir’s type, depth, depositional environment or the diagenetic history; the trap’s geometry, type or mechanism; the fluid’s type, properties or composition; the recovery method’s type or period; and the production history length, it is proved that three major technical and two non-technical factors are controlling the success of any field development plan. These are: reservoir heterogeneity, fault transmissibility, fracture effect, integration of people, data and managers and human resources. The targets of this paper are to highlight the major challenges modelers will face while characterizing and modeling their reservoirs and recommending the best solutions to overcome these challenges. Understanding these challenges benefits an integrated system for assisting in management of reservoir assets and demonstrates the latest appropriate technologies to increase productivity of any asset team.
-
-
-
Parameter Sensitivity in Seismic Net Pay Workflow
By B. DuttonAn investigation to illustrate the relative importance of the controlling factors in estimating seismic net pay from colour-inverted band-limited impedance data has been performed. This was achieved by using a new, semi-automated implementation of the process, allowing the sensitivity of each of the key controls on the resulting net pay to be found quickly and easily. This automated workflow was run over a synthetic dataset varying different input parameters. The chi angle and the low frequencies used in building the tuning wedge were found to have the largest effect on the final volume. Using this technique on real datasets could greatly improve the understanding of the possible range of pay volumes, reducing risk and highlighting the key input parameters. The presentation will work through one manual iteration of the complete workflow, then show how this workflow can be automated. The results running the workflow on a synthetic dataset will be described and discussed.
-