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Identifying the potash reservoirs from seismic data by using convolution neural network, constrained by the waveform characteristics of potash reservoirs

Zhu Lei, Zhang Fanchang, Xu Xunyong, Xu Wanglin

Acta Geophysica

2023

Vol. 71, no. 6

2699--2714

Exploration of potash resources under complex geological condition is particularly important. However, it is difficult to establish characteristic equations for direct prediction, since there is no direct relation between potash content (PC) and seismic response. To solve this problem, this paper proposed a potash reservoir prediction method by a specially designed convolution neural network (CNN) structure to train the special waveform and petrophysical characteristics of potash reservoirs. Considering that the potash reservoirs and petrophysical characteristics are not a one-to-one mapping, the prediction procedure is divided into two parts. First, a CNN is constructed for potash reservoir prediction, according to the spatial waveform characteristics of potash reservoirs. The mapping between potash reservoirs and waveform characteristics is used to obtain the potash reservoir probability data by the soft-max function. Then, another CNN for PC prediction is built based on the petrophysical characteristics of potash reservoirs. Meanwhile, according to the Hadamard criterion, the petrophysical characteristics of potash reservoir are constrained by the waveform characteristics. The two CNN models are used to directly predict the PC synergistically. Consequently, the bidirectional mapping problem can be alleviated and a loss function of the PC prediction CNN constrained with the waveform is obtained. Finally, by tuning the PC prediction CNN through the loss function, PC prediction is performed. The correlation between the predicted and true PC values can reach more than 80%.

Enhanced biosolubilization of mid-low grade phosphate rock by formation of microbial consortium biofilm from activated sludge

Xiao Chunqiao, Wu Xiaoyan, Zhu Lei, Yu Tong, Xu Zhenghe, Chi Ruan

Physicochemical Problems of Mineral Processing

2019

Vol. 55, iss. 1

217--224

Mid-low grade phosphate rock (PR) is a potential source of free phosphate to facilitate crop growth, but a cost effective and environmentally responsible extraction process is required. In this study, the capacity of a microbial consortium from activated sludge to solubilize PR in a laboratory-scale column reactor was investigated. The microbial consortium proved capable of efficiently releasing soluble phosphate in the reactor effluent over the 90-day trial. The microbial consortium grew well in the column system as evidenced by reduced chemical oxygen demand (COD) in the reaction solution. Biofilm formation was identified as critical for biosolubilization of the mid-low grade PR. Imaging of the biofilm by scanning electron microscopy (SEM) revealed a dense network of microbial cells embedded in extracellular polymeric substances (EPS). The biofilm contained both oxic and anoxic zones. The pH decreased significantly in both the biofilm and the reaction solution during operation, indicating healthy growth of the microbial consortium with corresponding acid generation and subsequent enhancement of phosphate solubilization.