Comparison of predicted properties of Ekofisk oils based on Crude Assay data - Evaluation of the predicted behaviour of satellites relative to previous studies.

ConocoPhillips Skandinavia ASpublishedVersio

Assessing the Potential to Detect Oil Spills In and Under Snow Using Airborne Ground-Penetrating Radar

With recent increased interest in oil and gas exploration and development in the Arctic comes increased potential for an accidental hydrocarbon release into the cryosphere, including within and at the base of snow. There is a critical need to develop effective and reliable methods for detecting such spills. Numerical modeling shows that ground-penetrating radar (GPR) is sensitive to the presence of oil in the snow pack over a broad range of snow densities and oil types. Oil spills from the surface drain through the snow by the mechanisms of unsaturated flow and form geometrically complex distributions that are controlled by snow stratigraphy. These complex distributions generate an irregular pattern of radar reflections that can be differentiated from natural snow stratigraphy, but in many cases, interpretation will not be straightforward. Oil located at the base of the snow tends to reduce the impedance contrast with the underlying ice or soil substrate resulting in anomalously low-amplitude radar reflections. Results of a controlled field experiment using a helicopter- borne, 1000-MHz GPR system showed that a 2-cm-thick oil film trapped between snow and sea ice was detected based on a 51% decrease in reflection strength. This is the first reported test of GPR for the problem of oil detection in and under snow. Results indicate that GPR has the potential to become a robust tool that can substantially improve oil spill characterization and remediation

Reducing oil droplet sizes from a subsea oil and gas release by water jetting a laboratory study performed at different scales

The main objective of subsea mechanical dispersion (SSMD) is to reduce the oil droplet sizes from a subsea oil release, thereby influencing the fate and behaviour of the released oil in the marine environment. Subsea water jetting was identified as a promising method for SSMD and imply that a water jet is used to reduce the particle size of the oil droplets initially formed from the subsea release. This paper presents the main findings from a study including small-scale testing in a pressurised tank, via laboratory basin testing, to large-scale outdoor basin testing. The effectiveness of SSMD increases with the scale of the experiments. From a five-fold reduction in droplet sizes for small-scale experiments to more than ten-fold for large-scale experiments. The technology is ready for full-scale prototyping and field testing. Large-scale experiments performed at Ohmsett indicate that SSMD could be comparable to subsea dispersant injection (SSDI) in reducing oil droplet sizes.publishedVersio

Subsurface oil releases - Verification of dispersant effectiveness under high pressure

The main objective with this project was to study possible pressure dependency of droplet formation in case of a subsea blow out of oil and the effectiveness of subsea dispersant injection (SSDI). The droplet sizes documented by the SINTEF Silhouette Camera from comparable experiments (nozzle, oil type, flow rates, injection techniques and dispersant product) at ambient conditions (5 meters depth) and high pressure conditions (175 bar or 1750 meters depth) show no significant difference in droplet sizes as a function of pressure. This lack of a pressure effect was observed for both formation of large droplets from untreated oil and formation of smaller droplets by dispersant injection (1 and 2% dispersant dosage). This strongly indicates that SSDI effectiveness is not significantly influenced by hydrostatic pressure. These experiments were performed using stabilized dead oil without gas. Experiments with recombined oil & natura! gas ("live oil") were performed in a study later in 2015 (Brandvik et al., 2016b ).The American Petroleum Institute - API JITF 03publishedVersio

Simulating dispersion of oils from a subsea release comparing mechanical and chemically enhanced dispersion — An experimental study of the influence of oil properties

The main objective with subsea mechanical dispersion (SSMD) is to influence the fate of an oil spill in the marine environment by significantly reducing oil droplet sizes from subsea release of oil. Earlier studies have indicated that the capability of SSMD to reduce oil droplet sizes is comparable to subsea dispersant injection (SSDI). Earlier testing of SSMD has mainly used a low viscus paraffinic oil. Focus for this study was to study SSMD and SSDI effectiveness using five oil types spanning out a wide variation of relevant oil properties. Effectiveness was quantified as the reduction in oil droplet sizes measured by a Silhouette camera. Testing of the two technologies were completed in the same experiment on a simulated subsea release. The results show a variation in effectiveness for both technologies as a function of oil properties. SSMD and SSDI showed comparable effectiveness for all oils tested.publishedVersio

Large-scale basin testing to simulate realistic oil droplet distributions from subsea release of oil and the effect of subsea dispersant injection

Small-scale experiments performed at SINTEF, Norway in 2011–12 led to the development of a modified Weber scaling algorithm. The algorithm predicts initial oil droplet sizes (d50) from a subsea oil and gas blowout. It was quickly implemented in a high number of operational oil spill models used to predict fate and effect of subsea oil releases both in academia and in the oil industry. This paper presents experimental data from large-scale experiments generating oil droplet data in a more realistic multi-millimeter size range for a subsea blow-out. This new data shows a very high correlation with predictions from the modified Weber scaling algorithm both for untreated oil and oil treated by dispersant injection. This finding is opposed to earlier studies predicting significantly smaller droplets, using a similar approach for estimating droplet sizes, but with calibration coefficients that we mean are not representative of the turbulence present in such releases.publishedVersio

Modernisation and updating of SINTEF Oil Weathering Model (OWM} - Extending and recalibration of the Crude Assay (CA) module in SINTEF OWM

SINTEF har siden åttitallet foretatt forvitringsstudier på en rekke oljetyper (både norske og utenlandske). Hovedmålsettingen med disse forvitringsstudiene har vært å predikere oljenes forvitringsegenskaper dvs. hvordan de oppfører seg på sjøen ved et eventuelt oljesøl (fordamping, emulgering, naturlig dispergering etc). Det ble i perioden 1997-99 utført et multivariabelt korrelasjonsstudie for Statoil av oljers sammensetting (Crude Assay (CA) data) og forvitringsegenskaper (data fra laboratoriestudier) som var generert hos SINTEF fram til 1997 (19 utvalgte oljetyper). En modell som beregner de input-data som SINTEFs Oil Weathering Model (OWM) trenger for å predikere oljens forvitringsegenskaper når forvitringsdata fra laboratoriet ikke er tilgjengelig, er etablert. Denne modellen ble også utvidet med et kalibreringssett bestående av 58 oljer gjennom et prosjekt finansiert av Statoil i 2005. Prosjektet beskrevet i denne rapporten har styrket modellen og gjort den mere generell, dvs gjeldene for en større gruppe av oljer ved å utvide kalibreringssettet til 141 oljer inkludert rafineriprodukter. Dette gjør at forvitringsegenskaper også for bunkersoljer kan predikeres basert på enkle parametre (viskositet, voks/asfalten, tetthet, stivnepunkt og kokepunktsprofilen). For å forbedre denne muligheten til å bruke SINTEF OWM direkte har dette prosjektet fokusert på: 1. Inkludere flere oljetyper/forvitringsstudier for å få flere oljer (totalt 141) i de enkelte klassene 2. Dele oljene inn i klasser (med/uten stivnepunktsproblemer, raffineriprodukter, meget voks/asfaltenrike) og predikere egenskapene innbyrdes i de enkelte klassene 3. Brukergrensesnitt med "warning messages" som gjør at modellen ikke kan brukes utenfor det området den er kalibrert for, samt angir forventet kvalitet på prediksjonene og "guiding messages" som hjelper brukeren å forstå hvordan CA-dataene kan brukes optimalt. 4. Det er ikke mulig å predikere forvitringsegenskaper basert på CA data fra lette raffeneriprodukter og kondensater. 5. Ny funksjonalitet "Find model oil" som rangerer oljer i oljedatabasen etter likhet med oppgitte CA data.Modernisation and updating of SINTEF Oil Weathering Model (OWM} - Extending and recalibration of the Crude Assay (CA) module in SINTEF OWMStatoil; Norwegian Coastal AssociationacceptedVersio

The use of wide-band transmittance imaging to size and classify suspended particulate matter in seawater

An in situ particle imaging system for measurement of high concentrations of suspended particles ranging from 30 μm to several mm in diameter, is presented. The system obtains quasi-silhouettes of particles suspended within an open-path sample volume of up to 5 cm in length. Benchmarking against spherical standards and the LISST-100 show good agreement, providing confidence in measurements from the system when extending beyond the size, concentration and particle classification capabilities of the LISST-100. Particle-specific transmittance is used to classify particle type, independent of size and shape. This is applied to mixtures of oil droplets, gas bubbles and oil-coated gas bubbles, to provide independent measures of oil and gas size distributions, concentrations, and oil-gas ratios during simulated subsea releases. The system is also applied to in situ measurements of high concentrations of large mineral flocs surrounding a submarine mine tailings placement within a Norwegian Fjord.publishedVersio