Normal Faulting and Volcanism in the Kora 3D Seismic Volume

<p>The spatial and temporal relationship between normal faulting and volcanism in offshore Western North Island, New Zealand can be used to gain insight into basin formation, hydrocarbon resources, regional tectonics, and large subduction processes. It is hypothesised that there is a causal relationship between volcanic activity and faulting, however, within the Taranaki Kora 3D seismic volume (survey) this relationship has not yet been explored. The overall aim of this thesis was to map and identify whether there is a relationship between volcanism and normal faulting within the Kora 3D survey. A causal relationship in location and timing between volcanic processes and fault activity was discovered in this study. Two novel models were created to explain the creation of the local stress leading to this causal relationship. The first model uses intrusive magma build up and the second extrusive cone building to explain the changes in local stress. These models not only support the causal relationship between volcanism and faulting activity but also provide a new understanding into how Kora volcanic cone activity may have influenced active faulting in the Kora 3D survey. Application of this new information will allow innovative insights into basin formation, regional and local tectonics, and subducting plate geometry in the Taranaki Basin. This research could be utilized to increase knowledge for prospecting and reduce geologic uncertainty, which is of importance for the New Zealand petroleum industry at this northern end of the Taranaki Basin.</p>

Normal Faulting and Volcanism in the Kora 3D Seismic Volume

<p>The spatial and temporal relationship between normal faulting and volcanism in offshore Western North Island, New Zealand can be used to gain insight into basin formation, hydrocarbon resources, regional tectonics, and large subduction processes. It is hypothesised that there is a causal relationship between volcanic activity and faulting, however, within the Taranaki Kora 3D seismic volume (survey) this relationship has not yet been explored. The overall aim of this thesis was to map and identify whether there is a relationship between volcanism and normal faulting within the Kora 3D survey. A causal relationship in location and timing between volcanic processes and fault activity was discovered in this study. Two novel models were created to explain the creation of the local stress leading to this causal relationship. The first model uses intrusive magma build up and the second extrusive cone building to explain the changes in local stress. These models not only support the causal relationship between volcanism and faulting activity but also provide a new understanding into how Kora volcanic cone activity may have influenced active faulting in the Kora 3D survey. Application of this new information will allow innovative insights into basin formation, regional and local tectonics, and subducting plate geometry in the Taranaki Basin. This research could be utilized to increase knowledge for prospecting and reduce geologic uncertainty, which is of importance for the New Zealand petroleum industry at this northern end of the Taranaki Basin.</p>

Uncertainty and Interpretability analysis of encoder-decoder architecture for channel detection

We have adopted a method to understand uncertainty and interpretability of a Bayesian convolutional neural network for detecting 3D channel geobodies in seismic volumes. We measure heteroscedastic aleatoric uncertainty and epistemic uncertainty. Epistemic uncertainty captures the uncertainty of the network parameters, whereas heteroscedastic aleatoric uncertainty accounts for noise in the seismic volumes. We train a network modified from U-Net architecture, on 3D synthetic seismic volumes, and then we apply it to field data. Tests on 3D field data sets from the Browse Basin, offshore Australia, and from Parihaka in New Zealand, prove that uncertainty volumes are related to geologic uncertainty, model mispicks, and input noise. We analyze model interpretability on these data sets by creating saliency volumes with gradient-weighted class activation mapping. We find that the model takes a global to local approach to localize channel geobodies as well as the importance of different model components in overall strategy. Using channel probability, uncertainty, and saliency volumes, interpreters can accurately identify channel geobodies in 3D seismic volumes and also understand the model predictions

Stochastic Oilfield Optimization Under Uncertain Future Development Plans

Summary Reservoir simulation is a valuable tool for performance prediction, production optimization, and field-development decision making. In recent years, significant progress has been made in developing automated workflows for optimization of production and field development by combining reservoir simulation with numerical optimization schemes. Although optimization under geologic uncertainty has received considerable attention, the uncertainty associated with future development activities has not yet been considered in field-development optimization. In practice, reservoirs undergo extensive development activities throughout their life cycle. Disregarding the possibility of future developments can lead to field-performance predictions and optimization results that might be far from optimal. This paper presents a stochastic optimization formulation to account for the uncertainty in future development activities while optimizing current decision variables (e.g., well controls and locations). A motivating example is presented first to demonstrate the significance of including the uncertainty in future drilling plans in oilfield-development optimization. Because future decisions might not be implemented as planned, a stochastic optimization framework is developed to incorporate future drilling activities as uncertain (random) variables. A multistage stochastic programming framework is introduced, in which the decision maker selects an optimal strategy for the current stage decisions while accounting for the uncertainty in future development activities. For optimization, a sequential approach is adopted whereby well locations and controls are repeatedly optimized until improvements in the objective function fall below a threshold. Case studies are presented to demonstrate the advantages of treating future field-development activities as uncertain events in the optimization of current decision variables. In developing real fields, where various unpredictable external factors can cast uncertainty regarding future drilling activities, the proposed approach provides solutions that are more robust and can hedge against changes/uncertainty in future development plans better than conventional workflows.

Multiscale uncertainty assessment in geostatistical seismic inversion

Geostatistical seismic inversion is commonly used to infer the spatial distribution of the subsurface petroelastic properties by perturbing the model parameter space through iterative stochastic sequential simulations/co-simulations. The spatial uncertainty of the inferred petroelastic properties is represented with the updated a posteriori variance from an ensemble of the simulated realizations. Within this setting, petroelastic realizations are generated assuming stationary and known large-scale geologic parameters (metaparameters), such as the spatial correlation model and the global a priori distribution of the properties of interest, for the entire inversion domain. This assumption leads to underestimation of the uncertainty associated with the inverted models. We have developed a practical framework to quantify uncertainty of the large-scale geologic parameters in geostatistical seismic inversion. The framework couples geostatistical seismic inversion with a stochastic adaptive sampling and Bayesian inference of the metaparameters to provide a more accurate and realistic prediction of uncertainty not restricted by heavy assumptions on large-scale geologic parameters. The proposed framework is illustrated with synthetic and real case studies. The results indicate the ability to retrieve more reliable acoustic impedance models with a more adequate uncertainty spread when compared with conventional geostatistical seismic inversion techniques. The proposed approach accounts for geologic uncertainty at the large scale (metaparameters) and the local scale (trace-by-trace inversion).