Innovative application of full-waveform inversion applied to extended wide-azimuth marine streamer seismic in a complex salt environment

We demonstrated the application of full-waveform inversion (FWI) guided velocity model building to an extended wide-azimuth towed streamer (EWATS) seismic data set in the Gulf of Mexico. Field data were collected over a historically challenging imaging area, colloquially called the “grunge zone” due to the formation of a compressional allosuture emplaced between two colliding salt sheets. These data had a poor subsalt image below the suture with conventional narrow-azimuth data. Additional geologic complexities were observed including high-velocity carbonate carapace near the top of salt and multiple intrasalt sedimentary inclusions. As such, improved seismic imaging was required to plan and execute wells targeting subsalt strata. Significant improvements to the velocity model and subsalt image were evident with wide-azimuth towed streamer and later EWATS data using conventional top-down velocity model building approaches. Then, high-impact improvements were made using EWATS data with an FWI velocity model building workflow; this study represented an early successful application of FWI used to update salt body geometries from streamer seismic data, in which many past applications were limited to improving sedimentary velocities. Later petrophysical data verified the new FWI-derived model, which had significantly increased confidence in the structural and stratigraphic interpretation of subsalt reservoir systems below the grunge zone.

Pharmacokinetics of the disialoganglioside, GD2, a circulating tumor biomarker for neuroblastoma, in nonhuman primates

Background: The ganglioside GD2 is a potential circulating tumor biomarker for the childhood cancer, neuroblastoma. Interpreting the levels of a circulating tumor biomarker depends in part on a knowledge of the biomarker’s clinical pharmacology. Background: The ganglioside GD2 is a potential circulating tumor biomarker for the childhood cancer neuroblastoma. Interpreting the levels of a circulating tumor biomarker depends in part on a knowledge of the biomarker’s clinical pharmacology. Methods: We studied the plasma and cerebrospinal fluid (CSF) pharmacokinetics of the C18 lipoform of GD2 in two nonhuman primates with indwelling subcutaneous CSF lateral ventricular reservoir systems. GD2 was quantified with a validated high-performance liquid chromatography (HPLC)/tandem mass spectrometry assay. GD2 was administered as a short intravenous infusion and frequent plasma and CSF samples were drawn over 72 hours. Results: GD2 plasma concentration declined monoexponentially with a half-life of 16 hours. Clearance was 0.0136 and 0.0131 L/h and volume of distribution (Vd) was 0.035 and 0.038 L/kg in the two animals. Vd was equivalent to plasma volume. Greater than 98% of GD2 in plasma is in a bound form consistent with its known association with lipoproteins and accounting for its limited volume of distribution. GD2 did not cross over from plasma into the CSF. Conclusions: The pharmacokinetic profile of GD2 is favorable for a circulating tumor biomarker. This study demonstrates the value of characterizing the clinical pharmacology of circulating biomarkers to better understand their clinical behavior.

Hydrodynamics Regulate Longitudinal Plankton Community Structure in an Alpine Cascade Reservoir System

Previous studies report significant changes on biotic communities caused by cascade reservoir construction. However, factors regulating the spatial–temporal plankton patterns in alpine cascade reservoir systems have not been fully explored. The current study explored effects of environmental factors on the longitudinal plankton patterns, through a 5-year-long study on the environmental factors and communities of phytoplankton and zooplankton in an alpine cascade reservoir system located upstream of Yellow River region. The findings showed that phytoplankton and zooplankton species numbers in the studied cascade reservoir system were mainly regulated by the hydrological regime, whereas nutrient conditions did not significantly affect the number of species. Abundance and biovolume of phytoplankton in cascade reservoirs were modulated by the hydrological regime and nutrient conditions. The drainage rate, N:P ratio, and sediment content in cascade reservoirs were negatively correlated with abundance and biovolume of phytoplankton. Abundance and biovolume of zooplankton were not significantly correlated with the hydrological regime but showed a strong positive correlation with nutrient conditions in cascade reservoirs. Shannon–Wiener index (H’) and the Pielou index (J) of phytoplankton were mainly regulated by the hydrological regime factors, such as drainage rate and sediment content in cascade reservoirs. However, temperature and nutrient conditions were the main factors that regulated the Shannon–Wiener index (H’) and the Pielou index (J) of zooplankton. Species number, abundance, and biovolume of phytoplankton showed a significant positive correlation with those of zooplankton. Hydrodynamics and nutrient conditions contributed differently in regulating community structure of phytoplankton or zooplankton. These findings provide an understanding of factors that modulate longitudinal plankton community patterns in cascade reservoir systems.

Application of an Optimization/Simulation Model for the Real-time Flood Operation of River-Reservoir Systems with One and Two-Dimensional Unsteady Flow Modeling

An application is presented of a new methodology for the real-time operation of flood control reservoir gate control operations of river-reservoir systems to minimize flooding. The methodology is based upon an optimization/simulation modeling approach that interfaces optimization with a one and/or two-dimensional unsteady flow simulation model (U.S. Army Corps of Engineers HEC-RAS). The approach also includes a model for short-term rainfall forecasting and the U.S. Army Corps of Engineers HEC-HMS model for rainfall-runoff modeling. Both short term forecasted rainfall in addition to gaged streamflow data and/or NEXRAD (Next-Generation Radar) can be implemented in the modeling approach. The optimization solution methodology is based upon a genetic algorithm implemented through MATLAB. The application is based upon the May 2010 flood event on the Cumberland River system in the USA, during which releases from Old Hickory dam caused major flooding downstream area of Nashville, Tennessee area. One of the major features of the modeling effort and the application presented was to investigate the use of different unsteady flow modeling approaches available in the HEC-RAS) including one-dimensional (1D), two-dimensional (2D), and the combined (1D/2D) approach. One of the major results of the application was to investigate the use the different unsteady flow approaches in the modeling approach. The 2D unsteady flow modeling is based upon the diffusion wave approach was found to be superior for the application to the Cumberland River system

Conditions for Effective Application of the Decline Curve Analysis Method

Determining the reliable values of the filtration parameters of productive reservoirs is the most important task in monitoring the processes of reserve production. Hydrodynamic studies of wells by the pressure build-up method, as well as a modern method based on production curve analysis (Decline Curve Analysis (DCA)), are some of the effective methods for solving this problem. This paper is devoted to assessing the reliability of these two methods in determining the filtration parameters of terrigenous and carbonaceous productive deposits of oil fields in the Perm Krai. The materials of 150 conditioned and highly informative (obtained using high-precision depth instruments) studies of wells were used to solve this problem, including 100 studies conducted in terrigenous reservoirs (C1v) and 50 carried out in carbonate reservoirs (C2b). To solve the problem, an effective tool was used—multivariate regression analysis. This approach is new and has not been previously used to assess the reliability of determining the filtration parameters of reservoir systems by different research methods. With its use, a series of statistical models with varying degrees of detail was built. A series of multivariate mathematical models of well flow rates using the filtration parameters determined for each of the methods is constructed. The inclusion or non-inclusion of these filtration parameters in the resulting flow rate models allows us to give a reasonable assessment of the possibility of using the pressure build-up method and the DCA method. All the constructed models are characterized by high statistical estimates: in all cases, a high value of the determination coefficient was obtained, and the probability of an error in all cases was significantly less than 5%. As applied to the fields under consideration, it was found that both methods demonstrate stable results in terrigenous reservoirs. The permeability determined by the DCA method and the pressure build-up curve does not control the flow of the fluid in carbonate reservoirs, which proves the complexity of the filtration processes occurring in them. The DCA method is recommended for use to determine the permeability and skin factor in the conditions of terrigenous reservoirs.

Application of Cellular Automata in Bi-Objective Operation of Multi Reservoir Systems

Optimal operation of multi-reservoir systems is one the most challenging problems in water resource management due to their multi-objective nature and time-consuming solving process. In this paper, Multi-Reservoir Parallel Cellular Automata-Simulated Annealing (MPCA-SA), a hybrid method based on cellular automata and simulated annealing is presented for solving bi-objective operations of multi-reservoir systems problems. The problem considers the bi-objective operation of a multi-reservoir system with the two conflicting objectives of water supply and hydropower generation. The MPCA-SA method uses two single-objective cellular automata acting in parallel to explore the problem search space and find the optimal solutions based on the probabilistic interaction with each other. Bi-objective operation of the Dez-Gotvand-Masjed Soleyman three-reservoir system, as a real-world system in southwestern Iran for a period of 60 months, is considered in order to evaluate the ability of the proposed method. In addition, a Non-dominated Sorting Genetic Algorithm (NSGAII) is also used to solve the problems and the results are compared with those of MPCA-SA, indicating the capabilities of the proposed MPCA-SA method. The results show that the MPCA-SA method is able to produce solutions comparable to those of NSGAII with a much-reduced computational cost equal to 1.2% of that required by the NSGAII, emphasizing the efficiency and practicality of the proposed method.