Shell's integrated quantitative interpretation workflow

2011 ◽  
Vol 51 (2) ◽  
pp. 681
Author(s):  
Frank Glass ◽  
Stephan Gelinsky ◽  
Irene Espejo ◽  
Teresa Santana ◽  
Gareth Yardley
Keyword(s):  
Seismic Data ◽  
Rock Properties ◽  
Well Log ◽  
Reservoir Properties ◽  
North West ◽  
The North ◽  
Fluid Properties ◽  
Well Data ◽  
Acoustic Responses ◽  
Carnarvon Basin

Shell Development Australia is a major asset holder in the Browse Basin and the Carnarvon Basin in the North West Shelf of Australia. In 2007, Shell Development Australia embarked on an integrated quantitative seismic interpretation project related to the Triassic Mungaroo Formation in the Carnarvon Basin. The main objective was to constrain the uncertainties in using seismic data as a predictor for rock and fluid properties of fields and prospects in the basin. This project followed a workflow that has been proven in other basins around the world, whereby the vertical and lateral variability of rock properties of both reservoir and non-reservoir lithologies are captured in general trends. The calculated trends are based on well log extractions of end member lithologies and the input of petrographic information and forward modelling. In combination with a regionally consistent 3D burial model for the estimation of remaining porosity, these established rock trends then allow for a prediction of various acoustic responses of reservoir and pore fill properties. The comparisons between the pre-drill predicted rock properties and the properties encountered after drilling at different reservoir levels have lead to a general confidence that the reservoir properties can be derived from seismic data where well data are not abundant. This increased confidence will play a major part in Shell’s attitude towards appraisal activities and decisions on various development options.

Accuracy of wavelets, seismic inversion, and thin-bed resolution

2017 ◽  
Vol 5 (4) ◽  
pp. T523-T530
Author(s):  
Ehsan Zabihi Naeini ◽  
Mark Sams
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Low Frequency ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Frequency Content ◽  
Frequency Model ◽  
North West ◽  
The North ◽  
Well Data

Broadband reprocessed seismic data from the North West Shelf of Australia were inverted using wavelets estimated with a conventional approach. The inversion method applied was a facies-based inversion, in which the low-frequency model is a product of the inversion process itself, constrained by facies-dependent input trends, the resultant facies distribution, and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness. The bandwidth of the seismic data is approximately 5–70 Hz, and the well data used to extract the wavelet used in the inversion are only 400 ms long. As such, there was little control on the lowest frequencies of the wavelet. Different wavelets were subsequently estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low-frequency seismic. The revised inversion showed greater gas-sand continuity and an extension of the reservoir at one flank. Noise-free synthetic examples indicate that thin-bed delineation can depend on the accuracy of the low-frequency content of the wavelets used for inversion. Underestimation of the low-frequency contents can result in missing thin beds, whereas underestimation of high frequencies can introduce false thin beds. Therefore, it is very important to correctly capture the full frequency content of the seismic data in terms of the amplitude and phase spectra of the estimated wavelets, which subsequently leads to a more accurate thin-bed reservoir characterization through inversion.

scholarly journals Geophysical imaging of porosity variations in the Danish North Sea chalk

2008 ◽  
Vol 15 ◽  
pp. 17-20 ◽  
Author(s):  
Tanni Abramovitz
Keyword(s):  
North Sea ◽  
Seismic Reflection ◽  
Seismic Inversion ◽  
Rock Properties ◽  
Well Log ◽  
Reservoir Properties ◽  
Seismic Reflection Data ◽  
Log Data ◽  
The North ◽  
The North Sea

More than 80% of the present-day oil and gas production in the Danish part of the North Sea is extracted from fields with chalk reservoirs of late Cretaceous (Maastrichtian) and early Paleocene (Danian) ages (Fig. 1). Seismic reflection and in- version data play a fundamental role in mapping and characterisation of intra-chalk structures and reservoir properties of the Chalk Group in the North Sea. The aim of seismic inversion is to transform seismic reflection data into quantitative rock properties such as acoustic impedance (AI) that provides information on reservoir properties enabling identification of porosity anomalies that may constitute potential reservoir compartments. Petrophysical analyses of well log data have shown a relationship between AI and porosity. Hence, AI variations can be transformed into porosity variations and used to support detailed interpretations of porous chalk units of possible reservoir quality. This paper presents an example of how the chalk team at the Geological Survey of Denmark and Greenland (GEUS) integrates geological, geophysical and petrophysical information, such as core data, well log data, seismic 3-D reflection and AI data, when assessing the hydrocarbon prospectivity of chalk fields.

scholarly journals Application of geophysical methods in the extrapolation of sedimentological data on unmastered areas of deposits (on the example of Pennsylvanian carbonate reservoir, Akanskoye oilfield, east of Russian Platform)

2021 ◽  
pp. 128-134
Author(s):  
B. V. Platov ◽  
◽  
A. N. Kolchugin ◽  
E. A. Korolev ◽  
D. S. Nikolaev ◽  
...  
Keyword(s):  
Seismic Data ◽  
Geophysical Methods ◽  
Russian Platform ◽  
Carbonate Reservoir ◽  
Reservoir Properties ◽  
Reservoir Characteristics ◽  
The North ◽  
Study Results ◽  
Core Study ◽  
Well Data

A feature of the oil-bearing carbonate deposits of the lower Pennsylvanian in the east of the Russian platform is their rapid vertical and horizontal change. It is often difficult to make correlations between sections, especially in the absence of core data when using only geophysical data. In addition, not all facies are reliably identified and traceable from log data and not all have high reservoir properties. Authors made an attempt to trace the promising facies both to adjacent wells and, in general, to the entire field area using core study results and translation of these results using log and seismic data. The data showed pinching of rocks with high reservoir characteristics in the direction of the selected profile (from south to north within the field). Coastal shallow water facies, represented by Grainstones and Packstones, with high reservoir properties in the south of the field, are replaced by lagoon facies and facies of subaerial exposures, represented by Wakestones and Mudstones with low reservoir characteristics, in the north of the field. The authors suggest that this approach can be applicable for rocks both in this region and for areas with a similar structure. Keywords: pinch-out; well data; seismic data; limestone; facies; reservoir rocks.

Creating detailed subsurface models using predictive image-guided well-log interpolation

2017 ◽  
Vol 5 (3) ◽  
pp. T279-T285 ◽  
Author(s):  
Parvaneh Karimi ◽  
Sergey Fomel ◽  
Rui Zhang
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Structural Information ◽  
Rock Properties ◽  
Well Log ◽  
Initial Model ◽  
The North ◽  
Structural Framework ◽  
Seismic Image ◽  
Seismic Reflectors

Integration of well-log data and seismic data to predict rock properties is an essential but challenging task in reservoir characterization. The standard methods commonly used to create subsurface model do not fully honor the importance of seismic reflectors and detailed structural information in guiding the spatial distribution of rock properties in the presence of complex structures, which can make these methods inaccurate. To overcome initial model accuracy limitations in structurally complex regimes, we have developed a method that uses the seismic image structures to accurately constrain the interpolation of well properties between well locations. A geologically consistent framework provides a more robust initial model that, when inverted with seismic data, delivers a highly detailed yet accurate subsurface model. An application to field data from the North Sea demonstrates the effectiveness of our method, which proves that incorporating the seismic structural framework when interpolating rock properties between wells culminates in the increased accuracy of the final inverted result compared with the standard inversion workflows.

CARNARVON BASIN ARCHITECTURE AND STRUCTURE DEFINED BY THE INTEGRATION OF MINERAL AND PETROLEUM EXPLORATION TOOLS AND TECHNIQUES

2002 ◽  
Vol 42 (1) ◽  
pp. 287 ◽  
Author(s):  
L.L. Pryer ◽  
K.K. Romine ◽  
T.S. Loutit ◽  
R.G. Barnes
Keyword(s):  
Seismic Data ◽  
Structural Model ◽  
Mineral Exploration ◽  
Petroleum Exploration ◽  
Block Rotation ◽  
North West ◽  
The North ◽  
Northern Carnarvon Basin ◽  
Migration Pathways ◽  
Carnarvon Basin

The Barrow and Dampier Sub-basins of the Northern Carnarvon Basin developed by repeated reactivation of long-lived basement structures during Palaeozoic and Mesozoic tectonism. Inherited basement fabric specific to the terranes and mobile belts in the region comprise northwest, northeast, and north–south-trending Archaean and Proterozoic structures. Reactivation of these structures controlled the shape of the sub-basin depocentres and basement topography, and determined the orientation and style of structures in the sediments.The Lewis Trough is localised over a reactivated NEtrending former strike-slip zone, the North West Shelf (NWS) Megashear. The inboard Dampier Sub-basin reflects the influence of the fabric of the underlying Pilbara Craton. Proterozoic mobile belts underlie the Barrow Sub-basin where basement fabric is dominated by two structural trends, NE-trending Megashear structures offset sinistrally by NS-trending Pinjarra structures.The present-day geometry and basement topography of the basins is the result of accumulated deformation produced by three main tectonic phases. Regional NESW extension in the Devonian produced sinistral strikeslip on NE-trending Megashear structures. Large Devonian-Carboniferous pull-apart basins were introduced in the Barrow Sub-basin where Megashear structures stepped to the left and are responsible for the major structural differences between the Barrow and Dampier Sub-basins. Northwest extension in the Late Carboniferous to Early Permian marks the main extensional phase with extreme crustal attenuation. The majority of the Northern Carnarvon basin sediments were deposited during this extensional basin phase and the subsequent Triassic sag phase. Jurassic extension reactivated Permian faults during renewed NW extension. A change in extension direction occurred prior to Cretaceous sea floor spreading, manifest in basement block rotation concentrated in the Tithonian. This event changed the shape and size of basin compartments and altered fluid migration pathways.The currently mapped structural trends, compartment size and shape of the Barrow and Dampier Sub-basins of the Northern Carnarvon Basin reflect the “character” of the basement beneath and surrounding each of the subbasins.Basement character is defined by the composition, lithology, structure, grain, fabric, rheology and regolith of each basement terrane beneath or surrounding the target basins. Basement character can be discriminated and mapped with mineral exploration methods that use non-seismic data such as gravity, magnetics and bathymetry, and then calibrated with available seismic and well datasets. A range of remote sensing and geophysical datasets were systematically calibrated, integrated and interpreted starting at a scale of about 1:1.5 million (covering much of Western Australia) and progressing to scales of about 1:250,000 in the sub-basins. The interpretation produced a new view of the basement geology of the region and its influence on basin architecture and fill history. The bottom-up or basement-first interpretation process complements the more traditional top-down seismic and well-driven exploration methods, providing a consistent map-based regional structural model that constrains structural interpretation of seismic data.The combination of non-seismic and seismic data provides a powerful tool for mapping basement architecture (SEEBASE™: Structurally Enhanced view of Economic Basement); basement-involved faults (trap type and size); intra-sedimentary geology (igneous bodies, basement-detached faults, basin floor fans); primary fluid focussing and migration pathways and paleo-river drainage patterns, sediment composition and lithology.

Drilling success as a result of probabilistic lithology and fluid prediction—a case study in the Carnarvon Basin, WA

2008 ◽  
Vol 48 (1) ◽  
pp. 31 ◽  
Author(s):  
Matthew Lamont ◽  
Troy Thompson ◽  
Carlo Bevilacqua
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Geological Model ◽  
Probabilistic Prediction ◽  
Individual Probability ◽  
Fluid Properties ◽  
Lithology Prediction ◽  
Well Data ◽  
Carnarvon Basin

The aim of quantitative interpretation (QI) is to predict lithology and fluid content away from the well bore. This process should make use of all available data, not well and seismic data in isolation. Geological insight contributes to the selection of meaningful seismic attributes and the derivation of valid inversion products. Uncertainty must be taken into account at all stages to permit risk assessment and foster confidence in the predictions. The use of the Bayesian framework enables prior knowledge, such as a geological model, to be incorporated into a probabilistic prediction, which captures uncertainty and quantifies risk. Nostradamus is a fluid and lithology prediction toolkit that forms part of a comprehensive QI workflow. It utilises a Bayesian classification scheme to make quantitative predictions based upon inverted seismic data and depth-dependent, stochastic rock physics models. The process generates lithology and fluid probability volumes. All available information is combined using geological knowledge to create a realistic pre-drill model. Separately, stochastically modelled multidimensional crossplots, which account for the uncertainty in the rock and fluid properties (based on petrophysical analyses of well data), are used to build probability density functions such as acoustic impedance (AI) vs Vp/Vs and LambdaRho vs MuRho. These are then compared to crossplots of equivalent inverted data to make predictions and quantitatively update the geological model. Individual probability volumes as well as a most-likely lithology and fluid volume are generated. This paper presents a case study in the Carnarvon Basin that successfully predicts fluids and lithologies away from well control in a way that effectively quantifies risk and reserves. Two of the three successful gas exploration wells were drilled close to dry holes.

Accurate Pseudo Log Prediction Using Machine Learning Based Automatic Log Regularization and Feature Augmentation Method

2021 ◽  
Author(s):  
Makky Sandra Jaya ◽  
Abdrahman Sharif ◽  
Ali Ahmed Reda Abdulkarim ◽  
Ghazali Ahmad Riza ◽  
Maleki Ali Hajian ◽  
...  
Keyword(s):  
Seismic Data ◽  
Field Data ◽  
Prediction Performance ◽  
Rock Properties ◽  
Training Dataset ◽  
Well Log ◽  
Standard Ml ◽  
Augmentation Strategy ◽  
Feature Augmentation ◽  
Well Data

Abstract Objectives/Scope: The performance of ML-based rock properties prediction from seismic with limited and sparse well data is very often inadequate. To address this limitation, we propose a novel automatic well log regularization (ALR) method with specially designed feature augmentation strategy to improve the prediction accuracy. The effectiveness of ALR method is showcased on field data in Malay basin where we successfully predict elastic logs with 30% higher accuracy, while using only 28% less training dataset. Methods, Procedures, Process: The ALR workflow (Figure 1): (1) feature selection and augmentation; (2) training and prediction and (3) prediction optimizations. The workflow starts with predicting any logs type which are available at training but not in blind wells using standard ML workflow for all blind wells (Step 1-2). Then, these intermediately predicted logs at blind well were jointly used as input features together with seismic-derived attributes using a specially designed feature augmentation strategy (Step 3). Finally, Step 1and 2 are then repeated to predict the elastic logs using these augmented input features. Results, Observations, Conclusions: The ALR method was applied on an oil/gas field data in Malay basin to predict elastic logs (AI and SI) at five blind wells from seismic data only and compared to the standard ML workflow. Two wells were used as training (28% of all data). The prediction performance of standard ML workflow (Figure 2a) is poor and can only capture general mean values of the actual AI/SI logs. The results of ALR workflow (Figure 2b) shows 30% better prediction performance compared to the standard ML workflow. In general, the background and high-resolution trend are well captured, and the overall prediction performance is improved using the new proposed prediction method. There are conceivably two explanations for this result: a) the background (low frequency) trend of the well log is properly reconstructed in ALR using only using seismic data. This could mainly lie in the ability of augmented features in better learning the uncertain reflection-reception relationship between seismic data and elastic logs, as well as the spatial/time-varying property of seismic data; (b) The ability to learn meaningful nonlinear feature relationship between input (feature) and output (label) variables with little or no supervision seems to work properly using specially designed feature augmentation. Novel/Additive Information: The ALR method is an ML-based pseudo log generation from seismic data using specially designed feature augmentation strategy. The novel ALR implementation relaxes the requirement of having a massive amount of high-quality labeled data for training and can therefore be applied in areas with limited well data information. ALR method is proven to be highly accurate for direct elastic logs prediction and can potentially be extended to estimate petrophysical properties from seismic data.

Evaluating the efficiency of using different variants of background models for inversion calculations

2020 ◽  
pp. 36-52
Author(s):  
I. A. Kopysova ◽  
A. S. Shirokov ◽  
D. V. Grandov ◽  
S. A. Eremin ◽  
E. N. Zhilin
Keyword(s):  
Seismic Data ◽  
Oil And Gas ◽  
Rock Properties ◽  
Elastic Parameters ◽  
Reservoir Properties ◽  
Acoustic Inversion ◽  
Well Data ◽  
Background Models ◽  
Effective Penetration

The use of the method of seismic data acoustic inversion, in the presence of thick gas cap, can lead to difficulties when building background models of elastic parameters. In this regard, in the conditions of acoustically contrast thin environments within the perimeter of the Russkoye oil and gas condensate field, in addition to the standard version based on the well data, the authors considered a number of modified techniques ("block", "flat", and background models). The use of these background models provided the best results and made it possible to significantly improve the quality of predicting rock properties; based on the drilling results, effective penetration was ensured at 66 %, which was 102 % of the plan. Also, based on the inversion results, it became possible to predict reservoir properties using the Bayesian lithotype classification method.

Multiphase oblique extension on the North West Shelf of Australia

2021 ◽  
Author(s):  
Chris Elders ◽  
Sara Moron
Keyword(s):  
Seismic Data ◽  
Lower Cretaceous ◽  
Passive Margin ◽  
Rift System ◽  
Active Deformation ◽  
North West ◽  
North East ◽  
The North ◽  
Northern Carnarvon Basin ◽  
Carnarvon Basin

<p>The North West Shelf of Australia has experienced numerous rift events during its prolonged evolution that most likely started in the Lower Palaeozoic and continued through to the formation of the present day passive margin in the Lower Cretaceous.  Carboniferous and Permian is associated with rifting of the Lhasa terrane, a phase extension in the Lower and Middle Jurassic associated with the separation of the Argo terrane Upper Jurassic to Lower Cretaceous extension culminated in the separation of Greater India and Australia.  Investigations based on interpretation of extensive, public domain seismic data, combined with numerical mechanical modelling, demonstrate that crustal structure, rheology and structural fabrics inherited from older events exert a significant control on the architecture of younger rifts.</p><p>Defining the older, more deeply buried rift episodes is challenging, but with seismic data that now images deeper structures more effectively, it is clear that NE-SW oriented Carboniferous to Permian aged rift structures control the overall geometry of the margin.  Variations in the timing, distribution and intensity of that rift may account for some of the complexity that governs the Triassic – a failed arm of the rift system might account for the accumulation of thick sequences of fluvio-delatic sediments in an apparent post-rift setting, while active deformation and igneous activity continued elsewhere on the margin.</p><p>A renewed phase of extension began in the latest Triassic in the western part of the Northern Carnarvon Basin, but became progressively younger to the NE.  High-resolution mechanical numerical experiments show that the dual mode of extension that characterises the Northern Carnarvon Basin, where both distributed and localised deformation occurs at the same time, is best explained by necking and boudinage of strong lower crust, inherited form the Permian rift event, proximal to the continental margin, and a subdued extensional strain rate across the distal extended margin.  A very clear and consistent pattern of ENE oriented extension, which interacts obliquely with the older NE-SW oriented Permian aged structures, is apparent across the whole of the Northern Carnarvon Basin and extends north east into the Roebuck and Browse Basins.  This is at odds with the NW-SE oriented extension predicted by the separation of the Argo terrane which occurs at this time.  This may be explained by the detached style of deformation that characterises the Mesozoic interval.  Alternatively, the separation of Greater India may have exerted a stronger influence on the evolution of the margin during the Jurassic than hitherto recognised.</p>

Seismic characterization of a blocky mass-transport deposit in the Trealla Limestone Formation, North Carnarvon Basin, Australia

2020 ◽  
Vol 8 (4) ◽  
pp. SR53-SR58
Author(s):  
Laura Ortiz-Sanguino ◽  
Javier Tellez ◽  
Heather Bedle ◽  
Dilan Martinez-Sanchez
Keyword(s):  
Mass Transport ◽  
Seismic Data ◽  
Information Management System ◽  
Data Set ◽  
Differential Dissolution ◽  
Passive Margins ◽  
The North ◽  
Seismic Characterization ◽  
The Individual ◽  
Carnarvon Basin

The deepwater Cenozoic strata in the North Carnarvon Basin, Australia, represent an interval of interest for stratigraphic studies in passive margins settings of mixed siliciclastic-carbonate environments. We have explored the geomorphological characteristics of a mass-transport deposit (MTD) within the Trealla Limestone Formation to describe in detail the differences among the blocks. To characterize the individual geometry and structural configuration of the blocks within the MTD, we used geometric seismic attributes such as coherence, curvature, dip azimuth, and dip magnitude using horizon slices and vertical profiles. The evaluation finds two types of blocks: remnant and glide (or rafted) blocks. Remnant blocks are in situ and stratigraphically continuous fragments with the underlying strata. This type of block is frequently fault-bounded and displays low deformation evidence. Glide blocks are part of the transported material detached from a paleoslope. These blocks are deformed and occasionally appear as “floating” fragments embedded within a chaotic matrix in the MTD. Glide blocks are used as kinematic indicators of the direction of deposition of MTDs. We evaluate these elements in a modern continental analog that resembles a similar setting for a better understanding of the slide occurrence. Geological feature: Glide blocks, North Carnarvon Basin, Australia Seismic appearance: Discrete angular blocks with internal reflectors Alternative interpretations: Differential dissolution in a mixed siliciclastic-carbonate environment Features with a similar appearance: Carbonate buildups, differential dissolution blocks Formation: Trealla Limestone Formation, North Carnarvon Basin Age: Early-Middle Miocene Location: Offshore Northwest Australia, North Carnarvon Basin Seismic data: Obtained from Western Australian Petroleum and Geothermal Information Management System, Draeck 3D seismic data set Analysis tools: Visualization software (Petrel 2019) and attribute performance software (AASPI 6.0)

Sign in / Sign up

Export Citation Format

Share Document