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Chris Page, EVP New Businesses Development, Viridien, explains how technologies used to support oil and gas exploration and development are enabling innovations in the energy transition and beyond.

Biosimulytics focuses on developing a platform that enables biopharma companies to shorten the time to market of new drug compounds by simulating lead optimization, one of the most challenging steps of the drug development process. This process relies on tedious laboratory experiments to crystallize and further characterize candidate drug molecules. Biosimulytics’ patented platform computes the most stable crystal structure, making drug development faster, more cost-effective and with less risk.

ELEM Biotech creates the fastest and most accurate virtual humans and virtual trials technology for the biomedical industry. Integrating its solutions in the development of new drugs and devices empowers companies to scale their capacity to test in human models, generate scientific evidence when it matters most, and de-risk innovation. ELEM Biotech’s human twins, crafted from real patient data, produce critical insights quickly and efficiently to support important decisions that protect patient and business interests. Solutions are cloud-deployed for easy access by pharmaceutical laboratories, medtechs or hospitals.

Erling Frantzen, Anna Lougon & Joe Zhou from our Earth Data team discuss how advanced geoscience technologies and data are successfully supporting energy companies in the search for hidden opportunities in the world’s hotspots.

Full-waveform inversion (FWI) has found great success in different geologic settings and has become a must-have tool for velocity model building (VMB), particularly in salt environments where geology and velocity are often highly complex. While still acoustic, FWI has already significantly improved salt models and marked a step-change in subsalt imaging compared to conventional VMB workflows driven by manual salt interpretation.

In areas of complex geology, strong impedance contrasts can generate highly elastic behavior leading to the breakdown of the acoustic assumption in FWI. In these cases, accurate Earth models cannot be obtained without considering the elastic wave equation. Many previous studies of elastic FWI typically focused on deep water areas where large salt structures generate elastic effects in the observed seismic data. In this article, we offer an alternative perspective on elastic FWI, highlighting its value over acoustic FWI in properly describing elastic effects observed in shallow-water environments, particularly around the chalk packages which are prevalent throughout the North Sea.

Brazilian pre-salt often exhibits geologically complex settings with many challenges for oil and gas exploration and production. One of these key challenges is the presence of igneous rocks. We analyze the ability of full-waveform inversion (FWI) to identify and detect this class of rock using an OBN data set from the Santos Basin. Comparisons between acoustic and elastic FWI are studied. Thanks to the improved physics, elastic FWI shows more accurate representations of the distribution and plumbing systems of igneous rocks in the pre-salt. Moreover, the resulting FWI Images show uplift over the classical reverse-time migration (RTM) images that have historically been used to image the field.

Full waveform inversion (FWI) is becoming an increasingly dominant force in velocity model building and seismic imaging, often providing us with unrivaled focusing and resolution of the subsurface image. The superior velocity models and seismic images achieved through FWI also enable serious and more meaningful discussions of uncertainties on FWI. While the Bayesian inference framework offers a general foundation for FWI uncertainty analysis, the high computational cost associated with classical algorithms, such as Monte Carlo methods, to sample the posterior distribution prohibits it from being applied to industrial-scale problems. The recent development of variational inference (VI) theory presents a promising alternative to traditional sampling algorithms, as it can generate reasonable estimations of the posterior distribution at a more affordable computational cost. In this abstract, we describe an FWI uncertainty analysis method based on a specific type of VI algorithm, the Stein variational gradient descent (SVGD). We demonstrate the efficacy and practicality of this method through 2D synthetic and 3D real data examples

Land seismic data in the Sultanate of Oman presents more and different challenges for full-waveform inversion (FWI) compared to marine data. This is mainly due to complex near-surface effects that create strong ground roll, which obscures already poor data quality, especially at lower frequencies. It also generates heavy multiple reverberations, particularly in the south of Oman, owing to very different interleaved lithologies that create shallow sharp velocity contrasts. This paper discusses the substantial improvements made to current methodologies in mitigating the effects of strong shallow heterogeneities. This results in more detailed high-resolution models that capture the complex velocity variations essential for accurate imaging.