Integrated reservoir characterization of a field from the North Sea: Part I. The rock physics model

1991 ◽  
Author(s):  
Sverre Strandenes ◽  
J. P. Blangy
Keyword(s):  
North Sea ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
The North ◽  
The North Sea ◽  
Physics Model ◽  
Rock Physics Model

scholarly journals Rock physics model of glauconitic greensand from the North Sea

2010 ◽  
Author(s):  
Zakir Hossain ◽  
Tapan Mukerji ◽  
Jack Dvorkin ◽  
Ida L. Fabricius
Keyword(s):  
North Sea ◽  
Rock Physics ◽  
The North ◽  
The North Sea ◽  
Physics Model ◽  
Rock Physics Model

scholarly journals Analysis of Bacterial Communities on North Sea Macroalgae and Characterization of the Isolated Planctomycetes Adhaeretor mobilis gen. nov., sp. nov., Roseimaritima multifibrata sp. nov., Rosistilla ulvae sp. nov. and Rubripirellula lacrimiformis sp. nov.

2021 ◽  
Vol 9 (7) ◽  
pp. 1494
Author(s):  
Sandra Wiegand ◽  
Patrick Rast ◽  
Nicolai Kallscheuer ◽  
Mareike Jogler ◽  
Anja Heuer ◽  
...  
Keyword(s):  
North Sea ◽  
Bacterial Communities ◽  
Aquatic Environments ◽  
The North ◽  
The North Sea ◽  
Epiphytic Communities ◽  
Different Strains ◽  
A Minor ◽  
The Phylum Planctomycetes

Planctomycetes are bacteria that were long thought to be unculturable, of low abundance, and therefore neglectable in the environment. This view changed in recent years, after it was shown that members of the phylum Planctomycetes can be abundant in many aquatic environments, e.g., in the epiphytic communities on macroalgae surfaces. Here, we analyzed three different macroalgae from the North Sea and show that Planctomycetes is the most abundant bacterial phylum on the alga Fucus sp., while it represents a minor fraction of the surface-associated bacterial community of Ulva sp. and Laminaria sp. Especially dominant within the phylum Planctomycetes were Blastopirellula sp., followed by Rhodopirellula sp., Rubripirellula sp., as well as other Pirellulaceae and Lacipirellulaceae, but also members of the OM190 lineage. Motivated by the observed abundance, we isolated four novel planctomycetal strains to expand the collection of species available as axenic cultures since access to different strains is a prerequisite to investigate the success of planctomycetes in marine environments. The isolated strains constitute four novel species belonging to one novel and three previously described genera in the order Pirellulales, class Planctomycetia, phylum Planctomycetes.

scholarly journals Metagenomic and geochemical characterization of pockmarked sediments overlaying the Troll petroleum reservoir in the North Sea

2012 ◽  
Vol 12 (1) ◽  
pp. 203 ◽  
Author(s):  
Othilde Håvelsrud ◽  
Thomas HA Haverkamp ◽  
Tom Kristensen ◽  
Kjetill S Jakobsen ◽  
Anne Rike
Keyword(s):  
North Sea ◽  
Petroleum Reservoir ◽  
Geochemical Characterization ◽  
The North ◽  
The North Sea

Hierarchical Bayesian lithology/fluid prediction: A North Sea case study

Geophysics ◽  
2012 ◽  
Vol 77 (2) ◽  
pp. B69-B85 ◽  
Author(s):  
Kjartan Rimstad ◽  
Per Avseth ◽  
Henning Omre
Keyword(s):  
North Sea ◽  
Rock Physics ◽  
Model Parameters ◽  
Gas Oil ◽  
Clear Fluid ◽  
Prior Model ◽  
Spatial Coupling ◽  
The North ◽  
Likelihood Model ◽  
Physics Model

Seismic 3D amplitude variation with offset (AVO) data from the Alvheim field in the North Sea are inverted into lithology/fluid classes, elastic properties, and porosity. Lithology/fluid maps over hydrocarbon prospects provide more reliable estimates of gas/oil volumes and improve the decision concerning further reservoir assessments. The Alvheim field is of turbidite origin with complex sand-lobe geometry and appears without clear fluid contacts across the field. The inversion is phrased in a Bayesian setting. The likelihood model contains a convolutional, linearized seismic model and a rock-physics model that capture vertical trends due to increased sand compaction and possible cementation. The likelihood model contains several global model parameters that are considered to be stochastic to adapt the model to the field under study and to include model uncertainty in the uncertainty assessments. The prior model on the lithology/fluid classes is a Markov random field that captures local vertical/horizontal continuity and vertical sorting of fluids. The predictions based on the posterior model are validated by observations in five wells used as blind tests. Hydrocarbon volumes with reliable gas/oil distributions are predicted. The spatial coupling provided by the prior model is crucial for reliable predictions; without the coupling, hydrocarbon volumes are severely underestimated. Depth trends in the rock-physics likelihood model improve the gas versus oil predictions. The porosity predictions reproduce contrasts observed in the wells, and mean square error is reduced by one-third compared to Gauss-linear predictions.

High-resolution reservoir characterization by an acoustic impedance inversion of a Tertiary deltaic clinoform system in the North Sea

Geophysics ◽  
2010 ◽  
Vol 75 (6) ◽  
pp. O57-O67 ◽  
Author(s):  
Daria Tetyukhina ◽  
Lucas J. van Vliet ◽  
Stefan M. Luthi ◽  
Kees Wapenaar
Keyword(s):  
North Sea ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Structural Information ◽  
Sampling Rate ◽  
Seismic Inversion ◽  
Acoustic Properties ◽  
The North ◽  
The North Sea ◽  
Well Data

Fluvio-deltaic sedimentary systems are of great interest for explorationists because they can form prolific hydrocarbon plays. However, they are also among the most complex and heterogeneous ones encountered in the subsurface, and potential reservoir units are often close to or below seismic resolution. For seismic inversion, it is therefore important to integrate the seismic data with higher resolution constraints obtained from well logs, whereby not only the acoustic properties are used but also the detailed layering characteristics. We have applied two inversion approaches for poststack, time-migrated seismic data to a clinoform sequence in the North Sea. Both methods are recursive trace-based techniques that use well data as a priori constraints but differ in the way they incorporate structural information. One method uses a discrete layer model from the well that is propagated laterally along the clinoform layers, which are modeled as sigmoids. The second method uses a constant sampling rate from the well data and uses horizontal and vertical regularization parameters for lateral propagation. The first method has a low level of parameterization embedded in a geologic framework and is computationally fast. The second method has a much higher degree of parameterization but is flexible enough to detect deviations in the geologic settings of the reservoir; however, there is no explicit geologic significance and the method is computationally much less efficient. Forward seismic modeling of the two inversion results indicates a good match of both methods with the actual seismic data.

Facies — The drivers for modern inversions

2020 ◽  
Vol 39 (2) ◽  
pp. 102-109
Author(s):  
John Pendrel ◽  
Henk Schouten
Keyword(s):  
Bayesian Analysis ◽  
Prior Information ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Rock Physics ◽  
Well Log ◽  
Data Set ◽  
Prior Probabilities ◽  
Physics Model ◽  
Rock Physics Model

It is common practice to make facies estimations from the outcomes of seismic inversions and their derivatives. Bayesian analysis methods are a popular approach to this. Facies are important indicators of hydrocarbon deposition and geologic processes. They are critical to geoscientists and engineers. The application of Bayes’ rule maps prior probabilities to posterior probabilities when given new evidence from observations. Per-facies elastic probability density functions (ePDFs) are constructed from elastic-log and rock-physics model crossplots, over which inversion results are superimposed. The ePDFs are templates for Bayesian analysis. In the context of reservoir characterization, the new information comes from seismic inversions. The results are volumes of the probabilities of occurrences of each of the facies at all points in 3D space. The concepts of Bayesian inference have been applied to the task of building low-frequency models for seismic inversions without well-log interpolation. Both a constant structurally compliant elastic trend approach and a facies-driven method, where models are constructed from per-facies trends and initial facies estimates, have been tested. The workflows make use of complete 3D prior information and measure and account for biases and uncertainties in the inversions and prior information. Proper accounting for these types of effects ensures that rock-physics models and inversion data prepared for reservoir property analysis are consistent. The effectiveness of these workflows has been demonstrated by using a Gulf of Mexico data set. We have shown how facies estimates can be effectively used to build reasonable low-frequency models for inversion, which obviate the need for well-log interpolation and provide full 3D variability. The results are more accurate probability-based net-pay estimates that correspond better to geology. We evaluate the workflows by using several measures including precision, confidence, and probabilistic net pay.

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