Forward modeling of fracture prediction based on seismic attribute modeling

Fractured reservoirs have always been a big favorable area for oil and gas reservoirs,so prediction of fractures is also a research hotspot in recent years.Due to the diversity of fracture development and the unclear development mechanism,fracture prediction has always been a major problem.Simple numerical simulation In this paper,seismic attribute is combined with numerical simulation,logging data and actual seismic profile are used as constraints,inversion impedance value and coherent attribute are combined,and finally a property model more in line with the actual geological conditions is established.The wave equation calculation and migration processing were used to obtain the numerical simulation profile,and the actual seismic profile,fracture detection profile and numerical simulation profile were combined for analysis:①The numerical simulation section under this modeling method can greatly correspond to the actual seismic section,and the reflected results can better reflect the changes of response characteristics.②The reliability and applicability of the fracture detection technology can be determined by comparing the forward simulation profile with the fracture detection profile.

Attributing Analysis on the Model Bias in Surface Temperature in the Climate System Model FGOALS-s2 through a Process-Based Decomposition Method

This study uses the coupled atmosphere–surface climate feedback–response analysis method（CFRAM） to analyze the surface temperature biases in the Flexible Global Ocean–Atmosphere–Land System model, spectral version 2（FGOALS-s2）in January and July. The process-based decomposition of the surface temperature biases, defined as the difference between the model and ERA-Interim during 1979–2005, enables us to attribute the model surface temperature biases to individual radiative processes including ozone, water vapor, cloud, and surface albedo; and non-radiative processes including surface sensible and latent heat fluxes, and dynamic processes at the surface and in the atmosphere. The results show that significant model surface temperature biases are almost globally present, are generally larger over land than over oceans, and are relatively larger in summer than in winter. Relative to the model biases in non-radiative processes, which tend to dominate the surface temperature biases in most parts of the world, biases in radiative processes are much smaller, except in the sub-polar Antarctic region where the cold biases from the much overestimated surface albedo are compensated for by the warm biases from nonradiative processes. The larger biases in non-radiative processes mainly lie in surface heat fluxes and in surface dynamics,which are twice as large in the Southern Hemisphere as in the Northern Hemisphere and always tend to compensate for each other. In particular, the upward/downward heat fluxes are systematically underestimated/overestimated in most parts of the world, and are mainly compensated for by surface dynamic processes including the increased heat storage in deep oceans across the globe.