Simultaneous multiple well-seismic ties using flattened synthetic and real seismograms

Wu, Xinming; Caumon, Guillaume

doi:10.1190/geo2016-0295.1

Cited by 25 publications

(7 citation statements)

References 31 publications

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“…biostratigraphy, seismic reflection surveys, lateral facies transitions, unconformities, onlaps) into the correlation process (e.g. Baville et al, 2022; Edwards et al, 2018; Julio et al, 2012; Wu & Caumon, 2017) have the potential to significantly improve a log‐based workflow like the one described here.…”

Section: Discussionmentioning

confidence: 99%

Automated multi‐well stratigraphic correlation and model building using relative geologic time

Sylvester

2023

Basin Research

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Stratigraphic correlation of geophysical well logs is one of the most important—and most time‐consuming—tasks that applied geoscientists perform on a daily basis. Using the dynamic time warping (DTW) algorithm, automated correlation of two wells is a fairly simple task; DTW can also be used to correlate a large number of wells along a single path. However, errors accumulate along a path and loops cannot be closed. To create a three‐dimensionally consistent correlation framework, we use a Python implementation of the Wheeler and Hale (2014) approach, which is based on the idea of stretching and squeezing all logs into a chronostratigraphic diagram that has relative geologic time (RGT) on its y‐axis. The depth shifts needed for the RGT transformation are computed by translating the outputs of a large number of pairwise DTW correlations into a least‐squares optimization problem that is solved through the conjugate gradient method. The resulting chronostratigraphic diagram provides an overview of the overall stratigraphy and its variability; and the correlation framework is significantly different from what one could get from correlating based on lithologic similarity between two logs. To create geologically intuitive well‐log cross sections, we use a multi‐scale blocking method that relies on the continuous wavelet transform to identify stratigraphic units of a certain scale in one well and then propagate these boundaries to all the other wells. We demonstrate the usefulness of this approach on a data set with close to 700 wells from the Permian Basin, West Texas. Linear channel bodies in the deepwater Spraberry Formation are easily detected and clearly highlighted in maps and cross sections. The methodology is robust enough for mapping subtle stratigraphic details, previously considered feasible only through manual interpretation. More importantly, it can be used to quickly build three‐dimensional stratigraphic models for large segments of sedimentary basins where enough log data are available.

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Section: Discussionmentioning

confidence: 99%

Automated multi‐well stratigraphic correlation and model building using relative geologic time

Sylvester

2023

Basin Research

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“…The DTW method is first proposed by Sakoe and Chiba (1978) in speech recognition, and then it is widely used in geophysics to correlate well logs (e.g., Smith and Waterman, 1980;Wu and Nyland, 1987;Julio et al, 2012;Wheeler and Hale, 2014; and seismic traces or images (e.g., Hale, 2013;Herrera and van der Baan, 2014;Wu and Caumon, 2017). DTW is robust to estimate correlation shifts in the presence of noise, and it is often more accurate than windowed crosscorrelation methods, especially in estimating rapidly varying shifts (Hale, 2013).…”

Section: Dynamic Time Warpingmentioning

confidence: 99%

Least-squares horizons with local slopes and multigrid correlations

Fomel

2018

GEOPHYSICS

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Most seismic horizon extraction methods are based on seismic local reflection slopes that locally follow seismic structural features. However, these methods often fail to correctly track horizons across discontinuities such as faults and noise because the local slopes can only correctly follow laterally continuous reflections. In addition, seismic amplitude or phase information is not used in these methods to compute horizons that follow a consistent phase (e.g., peaks or troughs). To solve these problems, we have developed a novel method to compute horizons that globally fit the local slopes and multigrid correlations of seismic traces. In this method, we first estimate local reflection slopes by using structure tensors and compute laterally multigrid slopes by using dynamic time warping (DTW) to correlate seismic traces within multiple laterally coarse grids. These coarse-grid slopes can correctly correlate reflections that may be significantly dislocated by faults or other discontinuous structures. Then, we compute a horizon by fitting, in the least-squares sense, the slopes of the horizon with the local reflection slopes and multigrid slopes or correlations computed by DTW. In this least-squares system, the local slopes on the fine grid and the multiple coarse-grid slopes will fit a consistent horizon in areas without lateral discontinuities. Across laterally discontinuous areas where the local slopes fail to correctly correlate reflections and mislead the horizon extraction, the coarse-grid slopes will help to find the corresponding reflections and correct the horizon extraction. In addition, the multigrid correlations or slopes computed by dynamic warping can also assist in computing phase-consistent horizons. We apply the proposed horizon extraction method to multiple 2D and 3D examples and obtain accurate horizons that follow consistent phases and correctly track reflections across faults.

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“…These 12 well logs are directly extracted from the corresponding density model. Before the conversion the well logs using the mappings computed from the seismic image, we first need to tie these well logs to the seismic image using manual or automatic methods (e.g., Muñoz and Hale, 2015;Wu and Caumon, 2016). The seismic well ties help to correlate the well-log values of some geologic layer with seismic reflectors that correspond to the same geologic layer.…”

Section: Flattening With Unconformitiesmentioning

confidence: 99%

Building 3D subsurface models conforming to seismic structural and stratigraphic features

2017

GEOPHYSICS

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Subsurface modeling from seismic and borehole data is important for reservoir prediction, geophysical exploration, and production. A reasonable model should honor borehole rock properties and conform to seismic structural and stratigraphic features. Such a subsurface model can be difficult to build in cases complicated by faults and unconformities. Automatic and semiautomatic methods have been proposed to build subsurface models from seismic and borehole data; however, seismic structural and stratigraphic features and borehole measurements are not fully used in most methods. I have developed a workflow to fully use seismic and borehole data to build subsurface models that honor borehole measurements and conform to seismic horizons, faults, unconformities, and stratigraphic features such as channels. In this workflow, I first automatically remove the faulting and folding in seismic and borehole data and map them into an unfaulted and flattened space, in which seismic reflectors and borehole measurements corresponding to the same geologic layers are horizontally aligned. I then build a subsurface model in this unfaulted and flattened space by computing a sequence of 2D horizontal interpolations of borehole data. Each horizontal interpolation is guided by the stratigraphic features apparent in the corresponding horizontal seismic slice, so that the interpolant conforms to the seismic stratigraphic features. I finally map the interpolated model back into the input space and obtain a subsurface model that honors the seismic and borehole data. I demonstrate the proposed workflow using synthetic and real examples complicated by faults and unconformities.

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Simultaneous multiple well-seismic ties using flattened synthetic and real seismograms

Cited by 25 publications

References 31 publications

Automated multi‐well stratigraphic correlation and model building using relative geologic time

Automated multi‐well stratigraphic correlation and model building using relative geologic time

Least-squares horizons with local slopes and multigrid correlations

Building 3D subsurface models conforming to seismic structural and stratigraphic features

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