Quantitative seismic interpretation of the Lower Cretaceous reservoirs in the Valdemar Field, Danish North Sea

Bredesen, Kenneth; Lorentzen, Mads; Nielsen, Lars; Mosegaard, Klaus

doi:10.1144/petgeo2021-016

Cited by 3 publications

(3 citation statements)

References 43 publications

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“…In the quantitative seismic interpretation study presented by Bredesen et al (2021), the reservoir quality of the Tuxen formation in the Valdemar Field was assessed using a Baysian pre-stack inversion method based on elastic well logs from BO-2X and BO-3X. We demonstrated how other wells within the area could be useful to include in the interpretation by predicting their Vs with the proposed MLPR model.…”

Section: Discussionmentioning

confidence: 99%

Estimation of shear sonic logs in the heterogeneous and fractured Lower Cretaceous of the Danish North Sea using supervised learning

Lorentzen

Bredesen

Mosegaard

et al. 2022

Geophysical Prospecting

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Shear wave velocity information is valuable in many aspects of seismic exploration and characterization of reservoirs. However, shear wave logs are not always available in the interval of interest due to cost and time‐saving purposes. In this study, we present a tailored supervised learning approach to estimate shear wave velocity from well‐log measurements in the Lower Cretaceous succession of the Valdemar and Boje fields in the Danish North Sea. Our objective is to investigate the performance of four supervised learning regression models (linear, random forest, support vector and multi‐layer perceptron). A limited well‐log data set from six wells is used for training and testing the supervised learning models. A set of well data containing normalized gamma ray, compressional wave velocity, neutron porosity and medium resistivity logs gave reasonable shear wave velocity estimates in the test wells with root‐mean‐square error scores within the range of other published studies. Based on limited input data and complex geology, the multi‐layer perceptron was the most successful model in predicting the reservoir sections of the test wells. However, all models lacked stability in the overburden zones. Lastly, re‐training the multi‐layer perceptron on the six wells to predict missing shear wave velocity in a nearby well showed promising results for further reservoir characterization. The obtained results can yield useful input into, for example, seismic pre‐stack inversion, amplitude versus offset analysis and rock physics analysis.

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Section: Discussionmentioning

confidence: 99%

Estimation of shear sonic logs in the heterogeneous and fractured Lower Cretaceous of the Danish North Sea using supervised learning

Lorentzen

Bredesen

Mosegaard

et al. 2022

Geophysical Prospecting

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“…Similarly, Uhlemann et al (2016) correlated the seismic velocities with seismic tomography to highlight the importance of the modulus of elasticity (M) for a better characterization in identifying potential hydrocarbon zones with seismic images of high resolution. Bredesen et al (2021) demonstrated how to perform a quantitative reservoir characterization using rock physics models on Source: Generated from Gavin (2015).…”

Section: Introductionmentioning

confidence: 99%

Seismic facies characterization using Rock Physics Templates and brittleness indices: Stybarrow field

López-Aguirre,

Domínguez-Cruz,

España-Pinto

et al. 2024

Geofis Int

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This paper proposes a method for identifying the lithological properties of the medium based on the joint analysis of the Lamé parameters, Young's Modulus, and Poisson's Ratio. Additionally, an analysis of brittleness was proposed to identify brittle/ductile intervals and areas of potential reservoirs. The petroelastic properties were analyzed at well and seismic scales using ternary rock physics templates. The ternary templates were built from a self-consistent micromechanical model. In addition, the analysis allows for preserving the conditions of the environment subsurface in the seismic and log information. A workflow for petroelastic lithology interpretation was coupled with a workflow of brittleness modeling. The results correlate well with conventional qualitative methodologies applied in previous studies. A brittleness analysis methodology was developed and tested to identify reservoirs associated with the Lower Cretaceous in the Stybarrow field in Australia; the results highlight the high brittleness zones attenuated by hydrocarbons ( ). The proposed seismic-based methodology is an improvement to conventional analysis trends for identifying lithologies and prospective hydrocarbon zones.

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“…The impact of the IR fraction on the geomechanical and rock physical properties of chalk is difficult to assert because it can be load bearing or in suspension within the pore space, and because the elastic properties of this clay-rich fraction are not well known. Knowledge of the elastic properties of this fraction is essential in the seismic prospecting phase, especially when performing quantitative seismic interpretation, which includes the derivation of porosity maps, determination of lithology and facies, and estimating saturating fluids (Bredesen et al, 2021). The elastic properties of the noncalcitic fraction also affect the mechanical properties of the rock, which impacts exploratory drilling (well stability and prediction of pore pressure) and field development (reservoir geomechanics: compaction/subsidence upon depletion).…”

Section: Introductionmentioning

confidence: 99%

Deriving mineral moduli of the noncarbonate fraction in a marly chalk reservoir using petrophysical logging data and an isoframe model

Meireles

Fabricius

2023

GEOPHYSICS

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The knowledge of the elastic properties of clays and clay-rich sediments is essential when performing quantitative seismic interpretation and geomechanical modelling of reservoirs where they are present. Such is the case of the marly chalk reservoirs of Lower Cretaceous age in the Danish North Sea. We present a new method to derive elastic properties of the clay-rich insoluble residue (IR) fraction in marly chalks, using petrophysical logs and rock physical modelling. We calculated compressional ( M), shear ( G), and bulk ( K) moduli of the Formation along the borehole using the density and sonic (shear and compressional) logs, and modelled the elastic properties of minerals using the Isoframe rock physics model. In our model, the marly chalk is composed of two materials: calcite, with well-known elastic properties, and the IR fraction, whose elastic properties are the sought variable. We systematically vary the assumed elastic properties of the IR fraction, each time achieving equality between measured and modelled elastic moduli solving for the Isoframe values of calcite ( IF c) and the IR fraction ( IF ir) for each of the three elastic parameters one at a time, deriving the modelled values for the other two. We add up the error between modelled and logged values for each set of assumed elastic properties of the IR fraction. We adopt the values of K ir and G ir that minimize the compound error as the actual elastic properties of the IR fraction. We ran the algorithm in the Boje-2c and Valdemar-2H wells in different stratigraphic units of the Lower Cretaceous: the Fanø Formation and the marly chalk of the Tuxen and Sola Formations. Elastic properties derived for the IR fraction compare well to data for wet clays from ultrasonic velocity laboratory tests. In a clean chalk section (nearly 100% calcite), the model outputs values similar to calcite.

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Quantitative seismic interpretation of the Lower Cretaceous reservoirs in the Valdemar Field, Danish North Sea

Cited by 3 publications

References 43 publications

Estimation of shear sonic logs in the heterogeneous and fractured Lower Cretaceous of the Danish North Sea using supervised learning

Estimation of shear sonic logs in the heterogeneous and fractured Lower Cretaceous of the Danish North Sea using supervised learning

Seismic facies characterization using Rock Physics Templates and brittleness indices: Stybarrow field

Deriving mineral moduli of the noncarbonate fraction in a marly chalk reservoir using petrophysical logging data and an isoframe model

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