Is Remote sensing a reliable technique in exploration of oil and gas?

The remote sensing images have characteristics of realty and macroscope that provide accurate and visual data for directly determining geometric shapes of sedimentary basins. The remote sensing techniques are more effective and useful for understanding and studying those basins in the out-of-the-way mountains and remote deserts, such as the Tarim basin in northwest China

It is important to develop a remote sensing technique for reliable detection of oil slicks for reasons of both oil exploration and environmental protection. Yet, unambiguous detection has proven an elusive goal. This article presents new thermal infrared spectra of oil slicks made from five different crude oil samples with a wide range of API gravities and compositions. After a brief outgassing phase, all oil slick spectra are quite similar and little affected by thickness, extended exposure to air or sunlight, and even by emulsification with seawater (mousse formation). Thus, oil slicks provide a remarkably unvarying spectral signature as remote sensing targets in the thermal infrared compared to other regions of the spectrum. This spectral signature in the 8–14 μm atmospheric window is flat, with an average reflectance of 4%. Seawater, on the other hand, has a spectrum that varies in reflectance with wavelength in the 8–14 μm window from 0.90 to 3.65%. In addition, we show that sea foam displays a reflectance spectrum quite similar to that of seawater in the 8–14 μm region, because the very high absorption coefficient of water in this wavelength region prevents volume scattering in foam bubbles. This results in a relatively uniform spectral background, against which oil slicks can be detected, based on their different spectral signature. Thus, thermal infrared multispectral remote sensing appears to offer a simple and reliable technique for aircraft or satellite detection of oil slicks.

Well, as we may know, Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object and thus in contrast to on site observation and RS have been around for several decades. sub-surface analyses have been more pervasive of several reasons.

before i try to put your mind RS for Oil and Gas Exploration, i want to mention modern Imaging Solutions including the following:

1. Satellite constellations that offer high revisit rates from providers such as Airbus Defense and Space.
2. New synthetic-aperture radar (SAR) sensors (e.g., Sentinel-1) delivering free or very-low-cost data.
3. Super-spectral sensors such as those aboard DigitalGlobe’s WorldView-3 satellite offer high spatial and spectral resolution with strategically placed bands in the SWIR range, which are excellent for mineral identification.
4. UAS platforms offering the ability to interchange payloads to support multi-modal collections.

these new data sources pave the way to think outside the box in how remote-sensing data are used across all disciplines within the O&G exploration. for example, the spatial and spectral resolution are important considerations for O&G remote-sensing analyses, temporal information and data fusion also add great value. New imagery is available almost anywhere on Earth at higher temporal resolution than ever before. The 16-day revisit time of Landsat-8 and Modis (ground-track repeat cycle) makes it possible to include time as a variable in regional-scale analyses at little to no cost. Higher-spatial-resolution imagery such as from the Pleiades sensors or WorldView-3 (and others) enables daily revisits for very granular time-sensitive analyses, such as tracking the size and scope of a spill or frequently monitoring a natural hazard or disaster that can impact operations.

But satellites aren’t the only platforms offering high revisit rates. The booming industry of unmanned aerial systems (UASs) enables revisit times often more than once per day, and perhaps equally as powerful is their ability to interchange the payload, making multimodal data fusion a common practice. UAS companies such as PrecisionHawk can image a site with high-resolution optical sensors as well as another sensor such as LiDAR or SAR, either at the same time with multi-payload systems or on the same day with a single interchangeable payload. Then analysis products such as spill delineations, volumetric measurements, building footprints, vegetation health maps and transportation corridors can be fused together to answer questions about the size and scope of disasters, proximity of population to thoroughfares, volumetric change, vegetation health and fault locations.

Finally; The myriad data modalities and resolutions now available mandate the need for modern and easy-to-consume analytics that are accessible within a powerful infrastructure. For example, using ENVI software, no matter what data format or source modality, the ingestion, processing, exploitation and dissemination of information products are seamless, because it uses an open architecture in which each individual data-processing task is consumable as a discrete process that accomplishes a very specific goal. These tasks are accessible as REST endpoints and are chained together to develop custom workflows aimed at solving specific problems. Research and development efforts are supported at the desktop, enabling real-time interaction with pixels so appropriate parameters are defined for each algorithm prior to generating the custom workflow.

 yes understanding what’s happening beneath Earth’s surface is important for accurate reservoir and flow modeling