Vikesh (2013), defines an attribute as a quality, property, or characteristic of somebody or something. A seismic attribute is a measurement derived from seismic data, usually based on measurements of time, amplitude, frequency, and/or attenuation (Sheriff, 2002) [2]. They may be time-based (related to structure) or amplitude-based (related to stratigraphy and reservoir characterization). These attributes are used to visually enhance or isolate features of prediction.

To define the distribution of the channelized sand features in Abu Madi paleo-valley and to show the structure pattern in the study area, seismic attributes (structure maps and horizon amplitude) were extracted on the Abu Madi Level 2 and 3 picked horizons.

Seismic amplitude is a post stack attribute which plays a major role in identifying lithology, geometry of sedimentary features and depositional setting. It is a measure of the contrast in properties between two layers. Maximum positive amplitude calculates the highest value of the amplitude.

Structure map is a type of subsurface map whose contours represent the elevation of a particular formation, reservoir or geologic marker in space, such that folds, faults and other geologic structures. Time structure map is a plot of the two-way-time of seismic signal to the surface of the horizon. Time-structure map can be converted into depth-structure maps using velocity. According to Asquith and Gibson (1982) [3], a hydrocarbon reservoir is considered to be a potential prospect if they are trapped within structural traps.

The seismic response is affected by the physical properties of pore fluids in a porous rock containing those fluids (Hussein, M., et al., 2020) [4]. AVO analysis has become prominent in the DHI (Direct Hydrocarbons Indicator) aimed at characterizing the fluid content or the lithology of a possible reservoir and reducing the exploration drilling risk (Chenin, J., 2020) [5].

The AVO technique has been developed by many researchers, such as Ostrander (1984) [6] and Rutherford and Williams (1989) [7] and all of them were started from the Aki-Richards equation (Stewart, R. R., 1990) [8], which is a practical approximation to the Zoeppritz equation (Zoeppritz, 1919) [9] for the reflection coefficient at the reflection interface.

The following formula is the two-term Shuey approximation to the Zoeppritz equations, which represents the angular dependence of P-wave reflection coefficients with two parameters: the AVO intercept (A) and the AVO gradient (B). In practice, the AVO intercept is a band-limited measure of the normal incidence amplitude, while the AVO gradient is a measure of amplitude variation with offset. Assuming appropriate amplitude calibration, A is the normal incidence reflection coefficient and B is a measure of offset-dependent reflectivity (Shuey, 1985) [10].

R(θ) ≈ A + Bsin²θ

where: θ is the incidence angle, R(θ) is the reflection coefficient at θ, A is the AVO intercept and B is the AVO gradient.

Well to seismic tie was performed using the available logs of Well 3 and seismic data to study the phase and polarity of seismic data (Figure 3). The seismic data has a zero phase and European polarity. So the Abu Madi Level 2&3 were interpreted on the seismic sections in a right way. Since faults are very important in the petroleum exploration industry, they were picked on the full-angle stack seismic sections (Figure 4). These faults in this area are normal faults and have a generally N-S trend.

The Maximum positive amplitude is extracted from the full-angle stack seismic data in the time intervals from 10 ms above to 10 ms below each horizon of AML2 &3. The amplitude maps of AML 2&3 shows the sand distribution within the area which are characterized by fluvio-deltaic sandstones (Figure 5).

Figure 6 shows the depth maps of these Abu Madi levels after time to depth conversion. When amplitude maps are compared to structure, they may indicate a direct hydrocarbon indicator, or DHI. The figure shows that the AML 2&3 reservoirs are conformable with the high structure. Also there are suggested locations to be drilled as a new remaining potentiality.

According to the AVO classification for gas sand reservoirs (Castagna and Swan 1998) [11], there are four classes for the classtic rocks. class I response is characterized by an increasing in impedance downward causing (decreasing in amplitude with increasing in incidence angle), class II has small normal incidence amplitude (+ or −), but the AVO leads to negative amplitudes at far offsets, class IIp where the zero incidence (or near offsets) is positive and therefore there is a polarity reversal at intermediate offsets, class III have large negative impedance contrast and negative gradient leads to increasing in amplitude with increasing in incidence angle, class IV has a large negative amplitude decreasing slightly with offset (Figure 7).

The reservoir sands of Abu Madi are characterized by acoustic impedance values that are lower than the encasing shale. Figure 8 highlights the AVO gradient analysis for the Abu Madi Level 2&3 gas anomalies. The prospective anomaly has the same AV response (AVO class III) as the gas bearing reservoirs anomalies in well X1 and X3.

Poisson’s ratio is one of the best indicators for the presence of gas saturated sands. Scaled poisons ratio AVO attribute shows variation based on the fluid content of the reservoir. (Castagna, J. P., 2001 and Foster et al., 2010) [12] [13] described that sands can have higher or lower acoustic impedance than surrounding shale, but gas sands have a lower poisons ratio than shale or brine sands. Ross (2002) [14] mentioned that this attribute works well for class II and III AVO responses. The derivative scaled Poisson’s ratio attribute can use in identifying the gas bearing sands and the prospective anomaly in the study area (Figure 9).

Castagna and Swan (1997) [15] show that the cross-plotting technique is the easiest method to derive the relationships between different variables. This technique is used in this paper to plot the AVO Intercept attribute on the X-axis and AVO gradient on the Y-axis.

The gas bearing anomalies and the prospective anomalies of Abu Madi Level 2&3 can be isolated from the background of the shale and brine sand and were plotted on the sections (Figure 10). The top of gas sand is in red color and the base of gas sand is in yellow color.