## 1 Introduction  
The importance of understanding of facies determination is a critical process in reservoir characterization [1]. It is the primary step that should be done before doing any petrophysical modeling [2]. The improvement of the resolution and cost efficiency using seismic technologies are essential in reservoir delineation and monitoring [3]. Integrating the well log and seismic on 3D seismic data are realized in analyzing the facies and fluid identification to reduce the uncertainty of interpretation in this area. The data integration by applying the amplitude versus offset (AVO)technique is suggested as a method in validating anomalies of seismic amplitude associated with gas sands [4]. AVO analysis is extensively used in lithology characterization, hydrocarbon detection, and fluid parameter analysis [5].  
The Northern Malay basin has a very complex reservoir, and several issues, i.e., particularly in reservoir distribution. The problems have occurred in the study area are related to the depositional setting (fluvial to local marine), heterogeneity in reservoir continuity and reservoir quality at numerous scales, the presence of low resistivity low contrast (LRLC) and radioactive sands in the Pliocene, as well as seismic challenges related to the presence of coal, shallow gas clouds and resolution issues [6]. The imaging of thin sand reservoir is also another issue that related to its resolution on the seismic [7]. The thickness of hydrocarbon pay zones is often 10 m or thinner. Moreover, the lithology of this field is composed of a siliciclastic, i.e., dominantly with interbedding sand and shale lithology.  
The facies identification on well log domain is predicted based on the integration of petrophysical property logs which is validated by core report [8]. The facies proposition is classified by using the cut-off of some logs e.g., volume of shale, volume of coal, water saturation, and porosity. In the seismic scale, the seismic AVO is extensively used in hydrocarbon prediction and fluid parameter studies [5]. The Scaled Poisson's Ratio attribute is commonly used in hydrocarbon and facies separation.  
The scale of quality factor of P-wave (SQp) and scale of quality factor of S-wave (SQs) methods have been successfully applied for fluid and hydrocarbon prediction in well log scale and pre-stack inversion [9; 10; 11; 12]. In the well log, the SQp attribute has the highest correlation with gamma-ray, while SQs attribute has the highest coefficient correlation with resistivity [11]. These methods are produced from the elastic properties parameters, which can also be applied to seismic through an elastic inversion process. In this research, SQp and SQs are attempted to be generated in AVO attribute that are obtained from intercept and gradient, which can be an alternative in facies and hydrocarbon identification. Whereas the AVO attribute is the effective tools in hydrocarbon indicator and lithology identification.  
The research aim is to introduce the alternative AVO attributes that are produced from intercept (A) and gradient (B), which are sensitive in facies and fluid classification/distribution. The alternative AVO attributes would use the data integration of well log and seismic data. New seismic attributes, i.e., SQp and SQs, would be applied in the reservoir target area that are aimed for giving better results in reducing uncertainty in reservoir characterization.