.png){kind=icon}
返回
Building large-scale density model via a deep-learning-based data-driven method
.png){kind=icon}
PRE
AI
DOI：10.1190/GEO2019-0332.1.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
As a rock-physics parameter, density plays a crucial role in lithology interpretation, reservoir evaluation, and description. However, density can hardly be directly inverted from seismic data, especially for large-scale structures; thus, additional information is needed to build such a large-scale model. Usually, well log data can be used to build a large-scale density model through extrapolation; however, this approach can only work well for simple cases and it loses effectiveness when the medium is laterally heterogeneous. We have adopted a deep-learning-based method to build a large-scale density model based on seismic and well log data. The long short-term memory network is used to learn the relation between seismic data and large-scale density. Except for the data pairs directly obtained from well logs, many velocity and density models randomly generated based on the statistical distributions of well logs are also used to generate several pairs of seismic data and the corresponding large-scale density. This can greatly enlarge the size and diversity of the training data set and consequently leads to a significant improvement of the proposed method in dealing with a heterogeneous medium even though only a few well logs are available. Our method is applied to synthetic and field data examples to verify its performance and compare it with the well extrapolation method, and the results clearly display that the proposed method can work well even though only a few well logs are available. Especially in the field data example, the built large-scale density model of the proposed method is improved by 11.9666 dB and 0.6740, respectively, in peak signal-tonoise ratio and structural similarity compared with that of the well extrapolation method.
Keyword:
WAVE-FORM INVERSION
NEURAL-NETWORKS
DECONVOLUTION
PREDICTION
TOOL
期刊
IF:
3.2
论文数:
8.4K
被引数:
3.3W
机构
引用论文
.png){kind=icon}
Spontaneous bowel perforation during the course of acute pancreatitis: a case report急性胰腺炎病程中的自发性肠穿孔：一例病例报告
OAAI
OAAI分享收藏Human Tracheobronchial Secretions: Development of Mucous Glycoprotein and Lysozyme-secreting SystemsOAAI
OAAI分享收藏Impact of Freeze-Drying on Cord Blood (CB), Serum (S), and Platelet-Rich Plasma (CB-PRP) Preparations on Growth Factor Content and In Vitro Cell Wound Healing冷冻干燥对脐带血（CB）、血清（S）和富血小板血浆（CB-PRP）制剂中生长因子含量及体外细胞伤口愈合的影响
OAAI
OAAI分享收藏分享收藏
查看更多内容