Petroleum Geo-Services (Norway)

Using the aerosol--aware Weather Research and Forecasting (WRF) model in an idealized tropical island framework, we examine how boundary layer moisture modulates the convective response to cloud condensation nuclei (CCN). Simulations across CCN concentrations of 30--2400 per cubic cm and varying relative humidity, CAPE and surface–flux regimes, show that convection consistently weakens with increasing CCN, but only when the boundary layer is sufficiently moist. In such a setting, fewer CCN yield larger droplets that rapidly convert to rain and reduce evaporation at mid-levels (between 2 and 4km), both of which warm and dry the layer and thereby weakening shallow convection. This limits vertical transport of moist static energy (MSE), allowing near-surface MSE and Convective Available Potential Energy (CAPE) to build up. As a result, subsequent deep convection in clean cases exhibits stronger updrafts, greater graupel production, and enhanced convective and mass fluxes. In contrast, humid but polluted environments yield numerous small drops which remain lofted and suppress warm rain, enhancing the evaporative source of vapor at mid-levels, strengthening shallow convection, limiting CAPE growth, and ultimately producing weaker convection.However, when the boundary layer is dry, both CAPE and convection show little sensitivity to CCN concentration, highlighting the role of moisture preconditioning. Satellite composites of TRMM convective intensity (measured by 40 dBZ echo top height) and MODIS droplet number (Nd) over tropical islands tentatively appear to support this mechanism. Higher Nd values are associated with lower CAPE and weaker convective vigor, with the strength of the trend being proportional to the near-surface relative humidity - consistent with simulations. Together, these results suggest that in a tropical island-setting, aerosols impact convection primarily when the boudary layer is preconditioned with sufficient moisture, and that under these conditions increased aerosol loading tends to suppress rather than invigorate deep convection.

The Southern Ocean is known to be one of the cloudiest places on Earth, and the important contribution of Southern Ocean clouds to Earth’s energy budget is undisputed. By changing their composition in response to warming, clouds in this region currently limit the rate of warming, as they become brighter with increasing temperature and thus exert a stabilising feedback on the climate system. Here, based on multiple lines of evidence, we show that in the current state of the Southern Ocean climate, this negative feedback happens to be maximised. Moving away from the present climate state in either direction (cooling or warming) will thus reduce the feedback, such that the climate sensitivity to any perturbation can be expected to grow rapidly with each degree of temperature change. This finding adds urgency to the implementation of effective climate mitigation to limit warming and thus preserve the stabilising climate effect of Southern Ocean clouds.

Abstract. Atmospheric turbulence and in particular its effect on tracer dispersion may be measured by cameras sensitive to the absorption of ultraviolet (UV) sunlight by sulfur dioxide (SO2), a gas that can be considered a passive tracer over short transport distances. We present a method to simulate UV camera measurements of SO2 with a 3D Monte Carlo radiative transfer model which takes input from a large eddy simulation (LES) of a SO2 plume released from a point source. From the simulated images the apparent absorbance and various plume density statistics (centre-line position, meandering, absolute and relative dispersion, and skewness) were calculated. These were compared with corresponding quantities obtained directly from the LES. Mean differences of centre-line position, absolute and relative dispersions, and skewness between the simulated images and the LES were generally found to be smaller than or about the voxel resolution of the LES. Furthermore, sensitivity studies were made to quantify how changes in solar azimuth and zenith angles, aerosol loading (background and in plume), and surface albedo impact the UV camera image plume statistics. Changing the values of these parameters within realistic limits has negligible effects on the centre-line position, meandering, absolute and relative dispersions, and skewness of the SO2 plume. Thus, we demonstrate that UV camera images of SO2 plumes may be used to derive plume statistics of relevance for the study of atmospheric turbulent dispersion.

Abstract The collection of high-resolution multibeam bathymetry off the tectonically controlled Tyrrhenian Calabrian margin (southern Tyrrhenian Sea) allowed us to recognize several mass-wasting processes, including shelf-indenting canyons and several landslide scars ranging over different spatial scales. In this paper, we aim to characterize two large submarine landslides (S1 and S2) affecting an area of c. 7 and 14 km 2 , respectively; both scars occur within water depths of 700–1000 m on slope gradients of 1.5−3°. S1 is interpreted as a disintegrative landslide, because most parts of the related landslide deposits were evacuated from the scar and are not recognizable on the present-day bathymetry, whereas the landslide deposits of S2 are well-preserved and mostly confined within the scar, indicating a different post-failure evolution. Based on the integration of multibeam bathymetry and single-channel seismic profiles, both the landslides are interpreted as translational failures, whereas their different post-failure behaviour has been associated with differences in material properties (inferred by headscarp morphology), depth of their failure plane and frontal confinement. We also suggest that thick contourite deposits recognized in the area may represent an important preconditioning factor for the development of these landslides, similarly to that observed in the nearby Capo Vaticano scar complex.

SummaryFluid‐driven fractures of brittle rock is simulated via a dual‐graph lattice model. The new discrete hydromechanical model incorporates a two‐way coupling mechanism between the discrete element model and the flow network. By adopting an operator‐split algorithm, the coupling model is able to replicate the transient poroelasticity coupling mechanism and the resultant Mandel‐Cryer hydromechanical coupling effect in a discrete mechanics framework. As crack propagation, coalescence and branching are all path‐dependent and irreversible processes, capturing this transient coupling effect is important for capturing the essence of the fluid‐driven fracture in simulations. Injection simulations indicate that the onset and propagation of fractures is highly sensitive to the ratio between the injection rate and the effective permeability. Furthermore, we show that in a permeable rock, the borehole breakdown pressure, the pressure at which fractures start to grow from the borehole, depends on both the given ratio between injection rate and permeability and the Biot coefficient.

ABSTRACT One of the major problems in the modeling and inversion of marine controlled-source electromagnetic (CSEM) data is related to the need for accurate representation of very complex geoelectrical models typical for marine environment. At the same time, the corresponding forward-modeling algorithms should be powerful and fast enough to be suitable for repeated use in hundreds of iterations of the inversion and for multiple transmitter/receiver positions. To this end, we have developed a novel 3D modeling and inversion approach, which combines the advantages of the finite-difference (FD) and integral-equation (IE) methods. In the framework of this approach, we have solved Maxwell’s equations for anomalous electric fields using the FD approximation on a staggered grid. Once the unknown electric fields in the computation domain of the FD method are computed, the electric and magnetic fields at the receivers are calculated using the IE method with the corresponding Green’s tensor for the background conductivity model. This approach makes it possible to compute the fields at the receivers accurately without the need of very fine FD discretization in the vicinity of the receivers and sources and without the need for numerical differentiation and interpolation. We have also developed an algorithm for 3D inversion based on the hybrid FD-IE method. In the case of the marine CSEM problem with multiple transmitters and receivers, the forward modeling and the Fréchet derivative calculations are very time consuming and require using large memory to store the intermediate results. To overcome those problems, we have applied the moving sensitivity domain approach to our inversion. A case study for the 3D inversion of towed streamer EM data collected by PGS over the Troll field in the North Sea demonstrated the effectiveness of the developed hybrid method.

ABSTRACT Migration of primary and multiple reflections leads to enhanced subsurface illumination and to increased image resolution. A joint migration approach using the complete wavefield requires properly imaged primaries and multiples of all orders. In recent works, primaries and multiples have therefore been imaged separately, using the upgoing and downgoing pressure wavefields obtained by decomposing dual-sensor streamer data. The matches between the corresponding depth images are still not found to be sufficiently accurate, so new and more appropriate imaging conditions need to be found. We reviewed the classical imaging approach used in one-way wave-equation migration, with the aim of extending it for simultaneous migration of primaries and all orders of multiples. Based on Rayleigh’s reciprocity theorem and well-known theoretical developments, we derived a new imaging condition described in terms of the upgoing pressure wavefield and a filtered version of the downgoing vertical-velocity wavefield. To evaluate the efficiency of this new imaging approach, primaries and multiples were separately migrated using synthetic and real data examples. These results were compared to those obtained using a conventional imaging condition. We found that the use of the new imaging condition led to a better match between the depth images and spectra of the migrated primaries and migrated multiples.

We develop a low-frequency dynamic effective medium for a horizontally layered transversely isotropic medium with vertical symmetry axis (VTI), and approximate this effective medium by a homogeneous VTI medium. This results in frequency-dependent anisotropy parameters valid for low frequencies and quasi-vertical propagation.

SummaryRecovery of oil from oil shales and the natural primary migration of hydrocarbons are closely related processes that have received renewed interest in recent years because of the ever tightening supply of conventional hydrocarbons and the growing production of hydrocarbons from low-permeability tight rocks. Quantitative models for conversion of kerogen into oil and gas and the timing of hydrocarbon generation have been well documented. However, lack of consensus about the kinetics of hydrocarbon formation in source rocks, expulsion timing, and how the resulting hydrocarbons escape from or are retained in the source rocks motivates further investigation. In particular, many mechanisms have been proposed for the transport of hydrocarbons from the rocks in which they are generated into adjacent rocks with higher permeabilities and smaller capillary entry pressures, and a better understanding of this complex process (primary migration) is needed. To characterize these processes, it is imperative to use the latest technological advances. In this study, it is shown how insights into hydrocarbon migration in source rocks can be obtained by using sequential high-resolution synchrotron X-ray tomography. Three-dimensional images of several immature “shale” samples were constructed at resolutions close to 5 μm. This is sufficient to resolve the source-rock structure down to the grain level, but very-fine-grained silt particles, clay particles, and colloids cannot be resolved. Samples used in this investigation came from the R-8 unit in the upper part of the Green River shale, which is organic rich, varved, lacustrine marl formed in Eocene Lake Uinta, USA. One Green River shale sample was heated in situ up to 400°C as X-ray-tomography images were recorded. The other samples were scanned before and after heating at 400°C. During the heating phase, the organic matter was decomposed, and gas was released. Gas expulsion from the low-permeability shales was coupled with formation of microcracks. The main technical difficulty was numerical extraction of microcracks that have apertures in the 5- to 30-μm range (with 5 μm being the resolution limit) from a large 3D volume of X-ray attenuation data. The main goal of the work presented here is to develop a methodology to process these 3D data and image the cracks. This methodology is based on several levels of spatial filtering and automatic recognition of connected domains. Supportive petrographic and thermogravimetric data were an important complement to this study. An investigation of the strain field using 2D image correlation analyses was also performed. As one application of the 4D (space + time) microtomography and the developed workflow, we show that fluid generation was accompanied by crack formation. Under different conditions, in the subsurface, this might provide paths for primary migration.Key words in this work include 4D microtomography, 3D image processing, shale, strain field analysis, kerogen, petroleum generation, primary migration, petrography, and thermogravimetry.

Oil exploration and production business decisions need accurate forecasts derived from a description of the subsurface combined with a statement of the uncertainty associated with that description. However, we commonly observe biases in the quantification of uncertainty due to cultural influence and overconfidence in our ability to estimate uncertainty, leading to disappointment when reality lies outside predictions. In tandem, a lack of insight into the value that uncertainty holds on the business case can lead to a mismatch between the effort expended on deriving a single “best” guess versus that on understanding the uncertainty range associated with that guess. Generating stochastic results around a “best technical case” can give a seemingly plausible range of uncertainty but typically fails to explore the uncertainty space.