Identifying and mitigating against potential seafloor and shallow drilling hazards at a complex Gulf of Mexico Deepwater site using HR3D seismic and AUV data

Kassarie, Kern; Mitchell, Stephen K.; Albertin, Martin; Hill, Andrew; Carney, Robert S.

doi:10.3997/1873-0604.2017026

Cited by 3 publications

(4 citation statements)

References 16 publications

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“…Studies by Kassarie et al . () and Ktenas et al . () show how this was done with VI in the southwestern Barents Sea.…”

Section: Methodsmentioning

confidence: 85%

“…The first step in a VI study is, therefore, to define an NCT model (set of NCT curves) from wells, as in Kassarie et al . (). This should be based on reference curves for normally pressured, water‐filled sections of the lithologies under study, that is, shale, sandstone and limestone.…”

Section: Methodsmentioning

confidence: 97%

“…), but FWI still does not achieve the vertical resolution that we seek for geohazard studies (Kassarie et al . ), and neither do other types of velocities derived from seismic processing. We evaluate a different set of velocity estimation methods, which aim for high vertical resolution rather than seismic imaging.…”

Section: Introductionmentioning

confidence: 97%

“…VI with standard‐resolution velocities is used for net apparent erosion studies (Kassarie et al . ; Ktenas et al . ).…”

Section: Introductionmentioning

confidence: 98%

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High‐resolution seismic velocity field estimation techniques and their application to geohazard, lithology and porosity prediction

Kalashnikova¹,

Meisingset²,

Øverås³

et al. 2020

Near Surface Geophysics

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A B S T R A C TSeismic velocity is an attractive parameter for geohazard interpretation, pore pressure analysis, play and prospect evaluations, and other geological studies, but ordinary seismic processing velocities often do not have a good enough resolution. We adapt a dynamic time warping algorithm to estimate geologically reasonable high-resolution velocities from average-quality seismic data that can be used for geohazard analysis based on 3D seismic data. To predict free gas and/or excess pore water pressure in thin shallow layers, we use velocity inversion. It is a method for simultaneous inversion of velocity data to geological attributes. It runs in the depth domain, uses a background velocity model for balancing of input velocities to wells and a normal compaction trend model to simultaneously estimate lithology, pore pressure and net apparent erosion attributes, while porosity is calculated from a sandstone-porosity relationship. The overall workflow is applied for geohazard analysis at two marine sites. The first example is a deep-water one from the Norwegian Sea, where thin and possibly overpressured or gas-filled layers are identified in the Pleistocene section. The second example is in a region with limestone-dominated lithology, where thin overpressured shales can cause severe drilling problems. In both examples, the thicknesses of the layers prone to geohazards are estimated to be about half of the wavelength. Dedicated high-resolution velocity estimations, such as those obtained through the proposed workflow with dynamic time warping, applied to standard 3D seismic data and followed by dedicated velocity inversion routines, are, therefore, a necessity for proper geohazard assessment.

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“…Studies by Kassarie et al . () and Ktenas et al . () show how this was done with VI in the southwestern Barents Sea.…”

Section: Methodsmentioning

confidence: 85%

Section: Methodsmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 97%

“…VI with standard‐resolution velocities is used for net apparent erosion studies (Kassarie et al . ; Ktenas et al . ).…”

Section: Introductionmentioning

confidence: 98%

See 2 more Smart Citations

High‐resolution seismic velocity field estimation techniques and their application to geohazard, lithology and porosity prediction

Kalashnikova¹,

Meisingset²,

Øverås³

et al. 2020

Near Surface Geophysics

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Identification and analysis of Salado Formation amplitude anomalies in the Midland Basin

Woller

Meek

George³

2022

The Leading Edge

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Careful mapping of shallow drilling hazards is key to operating an oil field safely and economically. In the Midland Basin, historical information indicates that shallow gas in the Salado Formation may result in blowouts. By using recently acquired higher-resolution 3D seismic surveys, we can identify circular high-amplitude anomalies that we interpret to be nitrogen-filled gas pockets. The larger pockets can be mapped and avoided before drilling a well. Detecting gas pockets in the Salado Formation may require modern 3D coverage or higher-resolution seismic drill site surveys if older low-fold seismic data are available at the drilling locations. The smallest pockets may not be detectable by any means. Although some of the larger anomalies are visible on older 3D surveys, most only became visible with the advent of higher-fold denser 3D seismic surveys. The anomalies sometimes follow a linear pattern. However, most are isolated in nature and appear as circular features in plan view and usually lenticular or columnar in section view. The anomalies range in size from a few traces in width (tens of feet or meters) to more than 1000 ft (300 m) in width or length. Seismic modeling suggests that the anomalies are very low P-wave velocity zones (about half of the velocity of the surrounding salt) and exhibit longer seismic traveltimes or push-down effects on reflections underneath the larger anomalies.

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Shallow Gas and Hydrate Hazard Prediction in the Gulf of Mexico Using a Probabilistic Machine Learning-Reservoir Simulation Workflow

Daigle

Jacoby

Carty

2022

Day 1 Mon, May 02, 2022

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In shallow marine sediments, gas accumulations and hydrates are significant geohazards to subsea infrastructure, drilling, and production. Therefore, predicting their occurrence is crucial to ensure offshore drilling safety and submarine infrastructure security. In this study, we generate predictions with uncertainty estimates with the goal of providing ageohazard assessment before any shallow hazard surveys are performed.We used a geospatial machine learning model to predict total organic carbon (TOC) and porosity at the seafloor in the northern Gulf of Mexico, and model sedimentation and consolidation in one dimension (1D) with microbial methanogenesis. Our model assumed that seafloor organic carbon is the source material for shallow hydrocarbon occurrences. The machine learning model outputs and uncertainties were sampled statistically to generate a suite of seafloor property realizations that were fed into our 1D model. Our predictions illustrate that gas and hydrate are more likely to be present along the shelf where seafloor TOC values are high, and are less likely to be present in deepwater areas (>500 m water depth) where seafloor TOC values are low. The results show that shallow water depth, lower sedimentation rate, and higher seafloor TOC are correlated with higher predicted gas saturations and shallower gas accumulation.Deepwater areas with significant reported oil production, such as AlaminosCanyon Block 857 (Great White), Green Canyon Block 640 (Tahiti/Caesar/Tonga), and Garden Banks Block 215 (Baldpate/Conger), are less likely to have shallow gas hazards. Any seafloor seeps identified in areas of high drilling activity likely originate from deep reservoirs, not from shallow gas accumulation.This work provides granular predictions of shallow geohazards on a basin scale and offers a holistic approach to identifying shallow hazards using big data and machine learning techniques. Leveraging geospatial machine learning models improves the predictions of subsurface hydrocarbons, despite sparse sampling of seafloor properties, and can be made pre-drill and without additional observations like sediment samples. This method can complement and augment existing hazard survey techniques.

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Identifying and mitigating against potential seafloor and shallow drilling hazards at a complex Gulf of Mexico Deepwater site using HR3D seismic and AUV data

Cited by 3 publications

References 16 publications

High‐resolution seismic velocity field estimation techniques and their application to geohazard, lithology and porosity prediction

High‐resolution seismic velocity field estimation techniques and their application to geohazard, lithology and porosity prediction

Identification and analysis of Salado Formation amplitude anomalies in the Midland Basin

Shallow Gas and Hydrate Hazard Prediction in the Gulf of Mexico Using a Probabilistic Machine Learning-Reservoir Simulation Workflow

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