Full-waveform inversion (FWI) utilizing long-offset ocean bottom node (OBN) data has become a key velocity model building tool for resolving complex velocities for deeper targets. Acquiring such OBN datasets with dense shot and receiver sampling remains costly. Sparse OBN data has been studied in recent years to reduce acquisition expense while maintaining desired benefits for FWI. Whereas sparse OBN data can provide velocities comparable to dense OBN data, it alone cannot provide seismic images and gathers fit for interpretation purposes. We demonstrate a cost-effective approach using joint sparse OBN and streamer FWI that effectively updates the deep velocity of a complex subduction zone in the Hikurangi margin near New Zealand's East Coast. The streamer data is then migrated to provide detailed and accurate images fit for interpretation.

Wenchang Field in the South China Sea contains a well-developed fault system, resulting in complex subsurface geology. Imaging the complex fault system plays an important role in hydrocarbon exploration in this area since the fault system forms a link between the source rocks and reservoirs. However, it is difficult to obtain a high-quality depth image of the fault system due to the effects of complex velocity and seismic absorption. Inaccurate depth velocities lead to fault shadows and structure distortions at the target zone. Absorption effects further deteriorate seismic imaging as they cause amplitude attenuation, phase distortion, and resolution reduction. We demonstrate how a combination of high-resolution depth velocity modeling and Q imaging work together to resolve these challenges. This workflow provides a step change in image quality of the complex fault system and targeted source rocks at Wenchang Field, significantly enhancing structure interpretation and reservoir delineation. A couple of commercial discoveries have been made, and several other potential hydrocarbon reservoirs have been identified based on the reprocessed data, which reveal new hydrocarbon potential in this region.

Summary Recently, there has been increasing interest in exploration of the Gulf of Papua (GoP), part of the Papuan Basin. This Basin has undergone a complicated structural and stratigraphic evolution related to its position on the north-eastern edge of the Australian plate. The presence of shallow absorbing anomalies, as well as complex tilted fault blocks and a mud volcano makes velocity model building and seismic imaging challenging. The image underneath such shallow gas anomalies suffers from considerable wavefield distortion and amplitude loss. There are also clear fault shadows and structural ambiguity underneath complex tilted fault blocks, as observed on the vintage PSTM seismic data. All these challenges are caused by the complexity of velocity and/or absorption (Q) fields. To overcome these challenges, we need to focus on two major aspects. Firstly, we need to derive a high-resolution velocity model. Full Waveform Inversion (FWI) is the state-of-art technology used to resolve velocity anomalies caused by shallow gas pockets. Supplemented by multilayer non-linear tomography, a high-resolution velocity model is obtained from shallow to deep. Secondly, we need to build a high-resolution absorption model. Frequency shift Q tomography and FWI guided Q tomography are applied to estimate the total absorption field, which is used in Q migration (QPSDM) to compensate for amplitude loss and phase distortion. A significant imaging uplift has been achieved by these technologies. The prominent improvement of interpretability of the new processed QPSDM seismic data will potentially enable a better understanding of hydrocarbon prospectivity in this area.

Non-linear slope tomography offers numerous effective solutions for velocity model building in complex geologies. One of its great advantages is the possibility to merge picks coming from common image gathers (CIGs) obtained on different velocity model. Here a new workflow of integrating selected CIG picking from different migration velocity for non-linear slope tomography is put forward to resolve large velocity errors associated with complex geology which can cause poor imaging or migration artifacts. We propose to first create a series of trial velocities from the initial velocity by varying its values inside poor imaging zones. Migrations are then applied using these trial velocities. The second stage involves CIG picking on these migrated gathers with tight constraints to ensure reliable picks. Following the process of non-linear slope tomography these CIG picks are then de-migrated to kinematic invariants with their corresponding trial velocities. The final stage is a joint tomographic inversion using all the invariants combined. The new workflow can bring more reliable information to the tomography inside complex geology where the S/N ratio is low and/or the initial velocity has large deviation from true velocity. As a result, it can give more reliable and robust velocity updates. Presentation Date: Wednesday, October 17, 2018 Start Time: 8:30:00 AM Location: 208A (Anaheim Convention Center) Presentation Type: Oral