Geostatistical modeling of petrophysical properties is a key step in modern integrated oil and gas reservoir studies. Recently, generative adversarial networks (GAN) have been shown to be a successful method for generating unconditional simulations of poreand reservoir-scale models. This contribution leverages the differentiable nature of neural networks to extend GANs to the conditional simula...

background: several reservoir systems have been constructed for hydropower generation around the world. hydropower offers an economical source of electricity with reduce carbon emissions. therefore, it is such a clean and renewable source of energy. reservoirs that generate hydropower are typically operated with the goal of maximizing energy revenue. yet, reservoir systems are inefficiently ope...

Background The SimTech Cluster of Excellence [1] studies multi-scale and multi-physics simulation methods. These methods aim for combining different scales (e.g. cells, tissue, bone, skeleton) and different physics (e.g. mechanics, thermodynamics, quantum physics) into one overall simulation. The Institute of Architecture of Application Systems (IAAS) has built a Workflow Management System (WfM...

Rock selection in modeling and simulation studies is usually based on two techniques; routinely defined rock types and those defined by special core analysis (SCAL). The challenge in utilizing these two techniques is that they are frequently assumed to be the same, but in practice, static rock-types (routinely defined) are not always representative of dynamic rock-types (SCAL defined) in the re...

Shale gas reservoir evaluation and production optimization both require geological models. However, currently, shale modeling remains relatively conventional does not reflect the unique characteristics of reservoirs. Based on a case study Fuling in China, an integrated workflow for reservoirs is proposed to facilitate its popularization application well improved quality comparability. This invo...

Inspired from the robust control principle, a robust scheduling method is proposed to solve uncertain scheduling problems. The uncertain scheduling problem is modeled by a set of workflow simulation models, and then a scheduling scheme (solution) is evaluated by the results of workflow simulations that are executed by using the workflow models in the set. A variable neighborhood immune algorith...