The influence of stratigraphy and facies distribution on reservoir quality and production performance in the Triassic Skagerrak Formation of the UK and Norwegian Central North Sea

Gray, Emmeline; Hartley, Adrian J.; Howell, John

doi:10.1144/sp494-2019-68

Cited by 10 publications

(2 citation statements)

References 43 publications

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“…This property was found to be a key parameter affecting recovery, in line with previous studies (e.g. Kjonsvik et al, 1994;Larue and Hovadik, 2008;Gray et al, 2022).…”

Section: Key Parameterssupporting

confidence: 90%

A Statistical Analysis of Geological and Engineering Predictors of Oilfield Performance Response: A Case Study of Oilfields on the Uk Continental Shelf

Osah,

Howell

2024

Journal of Petroleum Geology

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Oilfield production is controlled by a wide range of geological and engineering parameters, many of which are at least partially interrelated. This paper uses multivariate statistical methods (principal component analysis, regression analysis and analysis of variance) to determine how these parameters are related, and which of them are most significant in controlling and predicting oilfield performance. The analysis is based on a database of publicly available oilfield data from the United Kingdom Continental Shelf (UKCS), from which a series of geological, engineering and fluid‐related control variables from 136 fields were pre‐processed and analyzed. This dataset is a subset of a much wider project database for UKCS oil, gas and condensate fields. For this study, the project database was divided into two datasets: a first dataset with 10 parameters from 136 fields, and a second, more detailed dataset with 27 parameters from 38 fields. Both datasets were analysed using principal component analysis in order to investigate possible correlations between numerically/statistically interrogable predictor variables such as porosity, permeability, number of production wells, gas‐oil ratio and reservoir temperature. A regression analysis was then carried out on the predictor variables in order to obtain a ranking of predictability (i.e. how indicative a predictor is of a particular outcome) and sensitivity (how sensitive an outcome is to slight changes in a predictor) in relation to recovery factor based on R‐squared and regression coefficient values. The results showed that key variables from the principal component analysis included field size, number of production wells, PVT, gross depositional environment and reservoir quality. High‐ranking parameters of predictability and sensitivity from the regression analysis were found to include API, net‐to‐gross, porosity and reservoir depth. These results are consistent with previous studies and suggest that it should be possible to forecast oilfield recovery based on only a few selected input variables. As a preliminary test of forecasting ability of the variable permutations put forward, a best‐subsets multiple regression was carried out using a statistical software package and yielded results which corroborated the main findings.

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“…This property was found to be a key parameter affecting recovery, in line with previous studies (e.g. Kjonsvik et al, 1994;Larue and Hovadik, 2008;Gray et al, 2022).…”

Section: Key Parameterssupporting

confidence: 90%

A Statistical Analysis of Geological and Engineering Predictors of Oilfield Performance Response: A Case Study of Oilfields on the Uk Continental Shelf

Osah,

Howell

2024

Journal of Petroleum Geology

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“…The Zechstein deposits were also a major mobile substrate which controlled the distribution of reservoirs and structures in the CNS (Smith et al, 1993). Triassic rifting coupled with mobilization of the Zechstein salt created accommodation for major Triassic fluvial systems which form reservoirs in the Central Graben and the southern part of the Viking Graben (Gray et al, 2019).…”

Section: Geology Of the Ukcsmentioning

confidence: 99%

Spatial and temporal distribution of hydrocarbon production on the UK continental shelf

Osah,

Howell

2023

Resource Geology

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Hydrocarbon production from oil and gas fields is controlled by a variety of interconnected factors with a hierarchy of significance that is, for the most part, difficult to untangle. This article documents and investigates the spatial and temporal distribution of key hydrocarbon field parameters on the UK Continental Shelf. Data have been compiled from publicly available sources for 424 fields. Variables are considered as “descriptive parameters,” “control parameters” and “outcomes”. Descriptive parameters are metadata such as field name, location, etc. Control Parameters include depositional environment, present depth of burial, porosity, permeability, reservoir formation pressure, reservoir temperature, average net‐to‐gross, number of fault populations, hydrocarbon API, field area, bulk rock volume, well density, number of wells (production and injection), well spacing, gas oil ratio, reservoir thickness, fluid saturation, compartmentalization (quantitated by number of observable non‐communicating fault compartments), structural complexity (scaled from 0 to 5), field production strategy, trap type and stratigraphic heterogeneity. Outcomes are used to assess field performance and include final recovery factor (estimated), maximum production rate, and cumulative monthly production. Analysis of the database illustrates a number of empirical observations regarding hydrocarbon production on the UKCS. The Jurassic plays have been the most successful in the region in terms of total volumes produced while the Permian reservoirs of the SNS account for the majority of the gas. Most of the UKCS reservoirs record top depths between 2000 and 4500 m with good reservoir quality. The best reservoir quality is observed in reservoirs that were deposited within deep marine systems. The largest hydrocarbon reserves are found in the Northern North Sea basin in these deep marine (as well as paralic and shallow marine) reservoirs. Using the data from this article and affiliated data, potential exists for extracting insight beyond spatio‐temporal distributions.

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Stratigraphic palynology of the Middle–Late Triassic successions of the Central North Sea

Burgess

Jolley

Hartley

2020

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Historically, the continental Triassic successions of the Central North Sea have proven difficult to correlate, in part due to the poor palynomorph recovery associated with these sedimentary rocks. The existing framework for correlation is lithostratigraphic and, whilst this has proven effective in United Kingdom Continental Shelf (UKCS) Quad 30 where the mudstone members are well defined, elsewhere in the basin it is more problematic with confident identification of stratigraphic units becoming more difficult. Samples from 32 wells within UKCS Quads 22, 29 and 30, and Norwegian Quads 7, 15 and 16 underwent palynological analysis in which a processing method was utilized that was designed to concentrate palynomorph recovery from Triassic strata.The results of this analysis allowed the proposal of a new zonal scheme consisting of eight biozones. These biozones can then be used to correlate the Triassic successions of the Central North Sea (CNS), helping to provide both clarity and age constraint on previously disputed stratigraphic units, particularly the J-members of the Skagerrak Formation. Within the correlation framework outlined here, the Julius Mudstone Member is shown to be a productive horizon for palynomorph recovery, representing a widespread swamp environment. Here, its lateral extent is defined which is an important consideration when correlating the Triassic stratigraphy of the CNS given that this member can compartmentalize potential reservoirs contained within these successions. The stratigraphic palynology outlined here also allows clarity on the J-member equivalence of some of the informal units previously described within Triassic successions of the CNS, including the Marnock Shale and Heron Shale.

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The influence of stratigraphy and facies distribution on reservoir quality and production performance in the Triassic Skagerrak Formation of the UK and Norwegian Central North Sea

Cited by 10 publications

References 43 publications

A Statistical Analysis of Geological and Engineering Predictors of Oilfield Performance Response: A Case Study of Oilfields on the Uk Continental Shelf

A Statistical Analysis of Geological and Engineering Predictors of Oilfield Performance Response: A Case Study of Oilfields on the Uk Continental Shelf

Spatial and temporal distribution of hydrocarbon production on the UK continental shelf

Stratigraphic palynology of the Middle–Late Triassic successions of the Central North Sea

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