###### Abstract  
The high production potential of the Daqing oilfield in China is recognized for seismically thin sand bodies that usually are not resolved with conventional seismic data. The present study assesses the usefulness of applying seismic multi-attribute analysis to bandwidth extended data in resolving and making inferences about these thin layers. In thin layers, tuning can obscure relationships between seismic amplitude and rock properties. In such cases, the seismic phase varies with the layer impedance and may hence aid in reservoir characterization. A seismically derived relative geologic age may also be a useful attribute in predicting rock properties because it helps define the stratigraphic position of a layer. When utilized in multi-attribute analysis in the Daqing field, spectral decomposition amplitude, phase, and a relative geological age attribute to improved prediction of well log effective porosity from seismic data and are preferentially selected by stepwise regression. The study follows standard methodology by implementing seismic multi-attribute analysis and discusses the improvement of applying it to bandwidth extended data. This will include a combination of attributes such as relative geologic age, phase, amplitude, and the magnitude components of spectrally decomposed data. s +
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prediction accuracy and precision when using the spectrally broadened volume as input data. In that paper and this study, the spectrally broadened volume is obtained by sparse-layer inversion using basis pursuit decomposition [5]. The bandwidth extension algorithm is fully described and tested in [5] and theoretical aspects of the validity of the bandwidth extension are discussed and demonstrated in [6]. In this paper, our objective is to improve the accuracy and resolution of porosity prediction in the Daqing field, China, utilizing the spectral decomposition of bandwidth extended seismic data. The use of the seismic phase in rock properties prediction is investigated and the study introduces a novel seismic attribute termed relative geologic age. A comparison between predictions with spectral decomposition amplitude, magnitude, phase, and relative geologic age, in addition to the results obtained with conventional attributes--such as those utilized by [1] in the multi-attribute analysis--will be discussed. The Daqing field and, more specifically, the Qingshankou-Putahoa/Shaertu petroleum system have been broadly explored [7]. Hydrocarbons have been produced from thick reservoirs and potential has been identified on thinner layers [7] but it has been difficult to detect and correlate reservoirs that are significantly thinner than conventional seismic resolution, which is approximately \(\frac{1}{4}\) wavelength at the dominant frequency of the original seismic data (about 33 m for this dataset in the Daqing field). In the study area, well logs reveal hydrocarbon-bearing intervals with thicknesses ranging from 1 to 15 m that cannot be seismically resolved. The spectrally broadened seismic data has been previously shown to yield more accurate porosity predictions in this field ([PERSON] et al., 2020). Considering the reservoirs are greatly below the limit of seismic resolution for the original seismic data, bandwidth extended data are used as inputs to extract seismic attributes and evaluate the prediction improvement when using seismic attributes that are not usually employed for such purposes [1]. The present study specifically utilizes spectral decomposition amplitude, magnitude, and phase attributes and employs a relative geologic age volume derived from picked horizons. Then, constrained least squares spectral analysis [8] is implemented to perform spectral decomposition. The inputs to the multi-attribute analysis are the amplitude, magnitude, and phase attributes extracted at each frequency.