Estimation of base level changes in geological records is an important topic for petroleum geologists.Taking the Paleocene Upper Lingfeng Member of Lishui Sag as an example,this paper conducted a base level reconstruc...Estimation of base level changes in geological records is an important topic for petroleum geologists.Taking the Paleocene Upper Lingfeng Member of Lishui Sag as an example,this paper conducted a base level reconstruction based on Basin Filling Modelling(BFM).The reconstruction was processed on the ground of a previously interpreted seismic stratigraphic framework with several assumptions and simplification.The BFM is implemented with a nonlinear diffusion equation solver written in R coding that excels in shallow marine stratigraphic simulation.The modeled results fit the original stratigraphy very well.The BFM is a powerful tool for reconstructing the base level,and is an effective way to check the reasonableness of previous interpretations.Although simulation solutions may not be unique,the BFM still provides us a chance to gain some insights into the mechanism and dynamic details of the stratigraphy of sedimentary basins.展开更多
This paper describes the identification of waterflooded zones and the impact of waterflooding on reservoir properties of sandstones of the Funing Formation at the Gao 6 Fault-block of the Gaoji Oilfield,in the Subei B...This paper describes the identification of waterflooded zones and the impact of waterflooding on reservoir properties of sandstones of the Funing Formation at the Gao 6 Fault-block of the Gaoji Oilfield,in the Subei Basin,east China.This work presents a new approach based on a back-propagation neural network using well log data to train the network,and then generating a cross-plot plate to identify waterflooded zones.A neural network was designed and trained,and the results show that the new method is better than traditional methods.For a comparative study,two representative wells at the Gao 6 Fault-block were chosen for analysis:one from a waterflooded zone,and the other from a zone without waterflooding.Results from this analysis were used to develop a better understanding of the impact of waterflooding on reservoir properties.A range of changes are shown to have taken place in the waterflooded zone,including changes in microscopic pore structure,fluids,and minerals.展开更多
基金the Initial Fund for Young Scholars of Qingdao University of Science and Technology and the National Natural Science Foundation of China(No.51804325)。
文摘Estimation of base level changes in geological records is an important topic for petroleum geologists.Taking the Paleocene Upper Lingfeng Member of Lishui Sag as an example,this paper conducted a base level reconstruction based on Basin Filling Modelling(BFM).The reconstruction was processed on the ground of a previously interpreted seismic stratigraphic framework with several assumptions and simplification.The BFM is implemented with a nonlinear diffusion equation solver written in R coding that excels in shallow marine stratigraphic simulation.The modeled results fit the original stratigraphy very well.The BFM is a powerful tool for reconstructing the base level,and is an effective way to check the reasonableness of previous interpretations.Although simulation solutions may not be unique,the BFM still provides us a chance to gain some insights into the mechanism and dynamic details of the stratigraphy of sedimentary basins.
基金Project supported by the National Natural Science Foundation of China (No. 41172109)the National Natural Science Foundation of Shandong Province (No. ZR2011DM009)the Research Foundation for the Doctoral Program of Higher Education (No. 20110003110014),China
文摘This paper describes the identification of waterflooded zones and the impact of waterflooding on reservoir properties of sandstones of the Funing Formation at the Gao 6 Fault-block of the Gaoji Oilfield,in the Subei Basin,east China.This work presents a new approach based on a back-propagation neural network using well log data to train the network,and then generating a cross-plot plate to identify waterflooded zones.A neural network was designed and trained,and the results show that the new method is better than traditional methods.For a comparative study,two representative wells at the Gao 6 Fault-block were chosen for analysis:one from a waterflooded zone,and the other from a zone without waterflooding.Results from this analysis were used to develop a better understanding of the impact of waterflooding on reservoir properties.A range of changes are shown to have taken place in the waterflooded zone,including changes in microscopic pore structure,fluids,and minerals.
