Integration of Thermodynamics in Ensemble Modeling for Gas Development Project

Study was conducted to evaluate development of gas-bearing formations in the Azerbaijan sector of the Caspian Sea. Study considered subsea wellheads tied into subsea manifold, and that manifold tied to offshore facility. Flow Assurance required the calculation of subsea Flowing Wellhead Temperature (FWHT) and Pressures (FWHP). 242 subsurface scenarios were conducted with reservoir model. To accommodate all subsurface scenarios in flow assurance assessments, it was required to carry out FWHT/P calculations for all. Reservoir model was equipped with vertical lift performance curves for pressure loss calculations in tubing and logic for pressure loss estimation in subsea system. If correctly calculated, [FWHP >= dP(subsea) + Pseparator] logic should have been satisfied. As the reservoir model was not set for FWHT calculations, an external tool was required to cope with that task. Both nodal analysis software and dynamic flow modeling were considered as appropriate tools. However, as nodal modelling allowed much more automation, it was decided to use nodal analysis over dynamic modelling. To improve FWHP calculations: the logic was built into the reservoir model to: ○ estimate dP(subsea) from gas rate vs pressure drop curves ○ confirm validity of [minFWHP(wells 1, 2…n) >= dP(subsea) + Pseparator] statement: step was re-iterated until the statement was satisfied To improve FWHT calculations: Enthalpy Balance method was tested for gas wells with 1-2% error against actual data Then, nodal analysis models with the same method were built for the project wells Code was developed to calculate FWHT as part of the ensemble model predictions in following steps: ○ Well properties of each prediction step were transferred to nodal analysis software. ○ kH was varied until nodal analysis software calculated gas rate matched to ensemble model output within 1mmscf/d error Summary: Described methods allowed to significantly increase accuracy in FWHT and FWHP calculations and accommodate all possible subsurface scenarios in Flow Assurance evaluation Integration of subsea and topside hydraulics in subsurface modelling is important to develop flow assured design for development Enthalpy Balance temperature prediction method provides good match to actual data Use of coding provides huge opportunities to automate data analysis Paper will present different approach to calculation of FWHT and FWHP in subsurface modelling, integration of subsea and topside hydraulics in subsurface modelling via alternatives ways, use enthalpy balance temperature modelling, integration between nodal analysis and subsurface modelling and coding can prove analysis of large subsurface data set.

Software Sensors for Biomass Concentration Estimation in Filamentous Microorganism Cultivation Process

In this study, the potential of two software sensors for on-line estimation of biomass concentration during cultivation of filamentous microorganisms is examined. The first sensor is based on common bioreactor off-gas analyses, and uses the assumption of the biomass concentration linear dependence on the square root of cumulative O2 consumption. Parameters of the semi-empirical data-driven software sensor based on off-gas analysis were calculated from experimental cultivation data using linear regression. The second sensor is based on biocalorimetry, i.e., the on-line calculation of metabolic heat flux from general enthalpy balance of the bioreactor. The software sensor based on biocalorimetry thus essentially represents a model-driven approach, making use of a fundamental process model based on the enthalpy balance around the bioreactor. This approach has been combined with the experimental identification of the specific biomass heat production, which represents the main process-specific parameter of the software sensor based on biocalorimetry. For this sensor, the accuracy requirements on the process variable on-line measurements were also analysed. The experimental data from the pilot-scale antibiotics Nystatin production by a bacterium Streptomyces noursei were used to calculate the specific bioprocess heat production value using linear regression. The achieved results enabled us to propose a new on-line indicator calculated as the ratio of the outputs of both sensors, which can serve as a timely warning of the risk of undesired nutritional conditions of a culture characterized as underfeeding.