Exploration Insights October 2019 | Page 2

MULTI MARLS Predicting into the Unknown with Source-to- sink Scaling Relationships DATUM-2 Source-to-sink scaling relationships are emerging as a valuable predictive tool in frontier basins. This article outlines the method, applies it to the mid- Cretaceous MSGBC Basin, and discusses the potential pitfalls that exploration geologists need to consider. Controlling parameters: DATUM-2 Seismic 04 Accommodation Conceptual model (2D/3D) Outcrop Unravelling the Potential of the Namibe Basin Wells u a Sediment flux Sediment transport l Data (1D/2D/3D) Ahead of Angola’s 2019 offshore license round, we discuss the hydrocarbon potential of the Namibe Basin. Using the Neftex ® Insights portfolio, we pre-screen the blocks on offer, and identify the main play types and their associated risks, taking a closer look at the most prospective reservoirs — Cretaceous carbonates. r u i t c o f co n c e p n o t CONTENTS Processes 14 Editor Rebecca Head Editorial Advisors Subsurface iterative interpretation workflow Mike Simmons Big Picture Thinking to Highlight Exploration Risks Efficiently CLICK THE MAPS ABOVE TO EXPLORE SOLUTIONS Have you considered following a holistic Earth system science approach to highlight and understand the risks in the early exploration phases? Thomas Jewell Design and Circulation Stefanie Clayton On the cover: Sunset over the river, Nigeria. Image from Getty Images. Scan the QR code below and sign up to recieve our monthly digital magazine We believe that you cannot truly understand any element of the complex Earth System in isolation. Building on a robust temporal and spatial framework, we combine all of our understanding, data and data-driven models to deliver predictions on petroleum system presence and quality. Contact us today to find out more. This magazine is published by Halliburton Landmark. For comments and suggestions contact: [email protected]. Impedance Machine Learning in Petrophysics We have developed the Assisted Lithology Interpretation tool, which leverages geoscientists’ knowledge to generate accurate, rapid and consistent lithology interpretations from downhole petrophysical logs. It uses a supervised machine learning pipeline, which was built and tested using wells from the North West Shelf, Australia, and the Permian Basin, United States. 21 The Exploration Handbook — Forward Stratigraphic Modeling Numerical forward stratigraphic models support subsurface geological interpretation. They quantify the interaction of sediment supply and accommodation, and their effect on stratigraphic architecture, and are applicable both at the exploration and production scale. They form an essential part of the multi-proxy, iterative interpretation loop of the geology of the subsurface. 30