Hydrocarbon Resources of the Polish Outer Carpathians—Reservoir Parameters, Trap Types, and Selected Hydrocarbon FieldsA Stratigraphic Review

Author(s):  
Piotr S. Dziadzio ◽  
Zenon Borys ◽  
Stanisław Kuk ◽  
Emil Masłowski ◽  
Jaromir Probulski ◽  
...  
Author(s):  
Wojciech Gubała ◽  
Bronisław Wołoszyn

Bats hibernating in underground shelters of Małe Pieniny mountains (the Carpathian Mountains, Southern Poland) Six bat species were observed during winter censuses in years 2005-2009: Lesser horseshoe bat, Mouse-eared bat, Daubenton's bat, Whiskered/Brandt's bat, Northern bat and Brown long-eared bat. Rhinolophus hipposideros was most numerous (67% of all bats recorded). Largest hibernaculum on Polish side of range was mine Bania w Jarmucie, with maximum 29 bats during a single control, through the years of research number of species and individuals was increasing. Rarely seen in Outer Carpathians Eptesicus nilssonii winter roost was found in Homole Ravine Reserve.


2021 ◽  
pp. 1-18
Author(s):  
Gisela Vanegas ◽  
John Nejedlik ◽  
Pascale Neff ◽  
Torsten Clemens

Summary Forecasting production from hydrocarbon fields is challenging because of the large number of uncertain model parameters and the multitude of observed data that are measured. The large number of model parameters leads to uncertainty in the production forecast from hydrocarbon fields. Changing operating conditions [e.g., implementation of improved oil recovery or enhanced oil recovery (EOR)] results in model parameters becoming sensitive in the forecast that were not sensitive during the production history. Hence, simulation approaches need to be able to address uncertainty in model parameters as well as conditioning numerical models to a multitude of different observed data. Sampling from distributions of various geological and dynamic parameters allows for the generation of an ensemble of numerical models that could be falsified using principal-component analysis (PCA) for different observed data. If the numerical models are not falsified, machine-learning (ML) approaches can be used to generate a large set of parameter combinations that can be conditioned to the different observed data. The data conditioning is followed by a final step ensuring that parameter interactions are covered. The methodology was applied to a sandstone oil reservoir with more than 70 years of production history containing dozens of wells. The resulting ensemble of numerical models is conditioned to all observed data. Furthermore, the resulting posterior-model parameter distributions are only modified from the prior-model parameter distributions if the observed data are informative for the model parameters. Hence, changes in operating conditions can be forecast under uncertainty, which is essential if nonsensitive parameters in the history are sensitive in the forecast.


Author(s):  
Yu.R. Vladov ◽  
◽  
M.Yu. Nesterenko ◽  
Yu.M. Nesterenko ◽  
A.Yu. Vladova ◽  
...  

The predominant area of application of the developed methodology is the construction of the distribution of the geodynamic state of the developed hydrocarbon fields in oil and gas basin, and the identification of the corresponding distribution law. A number of the hydrocarbon deposits in terms of geological conditions of occurrence, structure and other parameters are geodynamically hazardous during their development. The Federal Law «On Subsurface Resources» (Article 24) requires conducting a complex of geological, surveying, and other observations sufficient for ensuring a normal technological cycle of work, and the prediction of hazardous situations. The developed methodology based on the construction of aggregated additive models for each reservoir and field is presented. It includes four sequential stages (24 operations): first — prepare geodynamic data; second — determine the geodynamic state of productive strata; third — find the geodynamic state of the developed deposits subsoil; fourth — build the distribution of the bowels geodynamic state of these fields for the entire oil and gas basin and identify the relevant distribution law. Oil and gas basin in the west of the Orenburg Region (Volga — Ural and Caspian oil and gas provinces) is considered as an example of implementation. Unique data of twenty geodynamic parameters of 320 productive strata (56 fields) were used. It is revealed that in accordance with the Pearson criterion, the theoretical data with a high confidence probability (95 %) correspond to the law of normal distribution. Developed methodology has significant technical and economic advantages, since it allows to identify the geodynamic state of productive strata and subsoil of the fields being developed, to identify hazardous geodynamic processes and to choose rational modes for the development of hydrocarbon deposits.


2021 ◽  
Author(s):  
V. Hladik ◽  
R. Prochac ◽  
M. Pereszlenyi ◽  
R. Berenblyum ◽  
A. Shchipanov ◽  
...  

2007 ◽  
Vol 42 (8) ◽  
pp. 1380-1386 ◽  
Author(s):  
B. Kozłowska ◽  
A. Walencik ◽  
J. Dorda ◽  
T.A. Przylibski

Sign in / Sign up

Export Citation Format

Share Document