Abstract. Delineating drainage networks is essential to predict surface water runoff, and consequently the flash flood hazards. Quantitative description of drainage basin and drainage network is confronted with problems related to the scale and resolution of the used topographic maps, and to the implemented systematic interpretation method. Integrated Geographic Information Systems (GIS), and remote sensing data overlaid on large-scale topographic maps, can efficiently be used to study the prevailed drainage network, and hence surface water potentiality. The developed integrated approach is applied for quantitative analysis of geomorphometeric parameters, and to delineate the watershed of Wadi Ghoweibba basin in Ain Sukhna area, western side of the Gulf of Suez, Egypt. Quantitative analysis of geomorphometeric parameters calculated for Wadi Ghoweibba basin is used to decipher the flash flood risk zones and to establish an effective hazard mitigation scheme.

Magnetic and seismic methods have been used in this study as complementary methods to each other to construct a geologic hazard map for Wadi Thuwal area. Magnetic interpretation for deep-seated geologic structures has involved reduction to pole algorithm and downward continuation techniques. It showed that there are three major fault trends: NE-SW and NNE-SSW, NW-SE, and N-S. Furthermore, shear zone has been found close to Harrat Thuwal, which was confirmed by the seismic method. Seismic method revealed three lithologic layers where the depth of the bedrock was found to be ranging between 9 m at the southeastern part of the study area and 24 m at its northern part. It showed also five major fault trends: NW-SE, ENE-WSW, NE-SW, and nearly E-W. Supported by the surface geology, magnetic and seismic results showed that the Wadi Thuwal area can be divided into three zones on the basis of geologic hazards, depending on the presence of geologic features such as faults. It is recommended that before any development plan in Wadi Thuwal area, the delineated hazard zonation should be taken into account.

The seismic amplitude versus offset (AVO) analysis has become a prominent in the direct hydrocarbon indicator in last decade, aimed to characterizing the fluid content or the lithology of a possible reservoir and reducing the exploration drilling risk. Our research discusses the impact of studying common depth point gathers on Near, Mid and Far-offsets, to verify the credibility of the amplitude response in the prospect evaluation, through analyzing a case study of two exploratory wells; one has already penetrated a gas-bearing sandstone reservoir and the second one is dry sand, but drilled in two different prospects, using the AVO analysis, to understand the reservoir configuration and its relation to the different amplitude response. The results show that the missing of the short-offset data is the reason of the false anomaly encountered in the dry sand, due to some urban surface obstacles during acquiring the seismic data in the field, especially the study area is located in El Mansoura city, which it is a highly cultivated terrain, with multiple channels and many large orchards on the edge of the river, and sugar cane and rice fields. Several lessons have been learned, which how to differentiate between the gas reservoirs and non-reservoirs, by understanding the relation between the Near and Far-offset traces, to reduce the amplitude anomalies to their right justification, where missing of Near-offset data led to a pseudo-amplitude anomaly. The results led to a high success of exploration ratio as the positives vastly outweigh the negatives.

No abstract

Seismic wavelets are dynamic components that result in a seismic trace when convolved with reflectivity series. The seismic wavelet is described by three components: amplitude, frequency, and phase. Amplitude and frequency are considered static because they mainly affect the appearance of a seismic event. Phase can have a large effect on seismic appearance by changing the way it describes the subsurface. Knowing the wavelet properties of certain seismic data facilitates the process of interpretation by providing an understanding of the appearance of regional geologic markers and hydrocarbon-bearing formation behavior. The process through which seismic data wavelets are understood is called seismic well tie. Seismic well tie is the first step in calibrating seismic data in terms of polarity and phase. It ensures that the seismic data are descriptive to regional markers, well markers, and discoveries (if they exist). The step connects well data to seismic data to ensure that the seismic correctly describes well results at the well location. It then extends the understanding of seismic behavior to the rest of the area covered by the seismic data. Good seismic well tie will greatly reduce uncertainties accompanying seismic interpretation. One important outcome of the seismic well tie process is understanding the phase of seismic data, which affects how seismic data will reflect a known geologic marker or hydrocarbon-bearing zone. This understanding can be useful in quantifying discoveries attached to seismic anomalies and extending knowledge from the well location to the rest of the area covered by seismic data.