Static Reservoir Modeling of the Eocene Clastic Reservoirs in the Q-Field,Niger Delta,Nigeria

Natural Resources Research - This work integrates seismic and well log data to establish a 3D reservoir model of the Q-Field, which is a prolific onshore hydrocarbon field situated in the Central...     

Evaluation of the ASL and Hawara formations using seismic- and log-derived properties, October Oil Field, Gulf of Suez, Egypt

October Field is one of the most prolific offshore oil fields in the Gulf of Suez of Egypt. It consists of a number of marine platforms and produces oil from different reservoirs of different geological ages from the Lower Cretaceous to the Miocene. The aim of this study was to enhance a seismic-log evaluational procedure to evaluate the Miocene-aged Asl and Hawara Formations which encounter the main hydrocarbon and source rock potentials in the area North of October Oil Field. The well logging data, the borehole seismic data, and the velocity surveys are all used in this study. A number of synthetic seismograms are constructed and interpreted together with the deduced seismic impedance and reflection coefficient data for many wells in the study area. In addition, a comprehensive velocity analysis is performed using the seismic times and the computed average and interval velocities. These seismic-derived parameters are primarily used in recognizing and locating precisely the marl and sand sections of Asl Formation which show low to middle amplitudes. Furthermore, a quantitative well logging analysis is carried out over Asl and Hawara Formations to shed light over their hydrocarbon potentiality. Good oil saturation is exhibited by the Asl sand section which reaches to more than 90% in the southern parts of the study area. The petrophysical characters of this sand are very good in terms of good effective porosity (9% to13%), low shale volume (V _sh?<?5%), and high oil saturation (S _h?>?85%). The sections of the Asl marl and the Hawara shale on the other hand are considered completely wet. An integrated model making use of the seismic- and log-derived properties is applied over the two studied formations for better understanding the reservoir of interest. Many relations are constructed between velocity, seismic impedance, and the rock pore spaces on one hand and between the velocity, lithology, and fluid content on the other hand. This study revealed that the sand section attains very good oil-bearing potentiality in the study area and proved that the application of an integrated model of the log- and seismic-derived properties led to an enhanced evaluation of the Asl and Hawara Formations, good discrimination between their lithological components besides precise differentiation from the overlying Middle to Late Miocene sections.     

A new evaluation of seismic hazard for the northwestern part of Saudi Arabia

Natural Hazards - A new evaluation of seismic hazard in the northwestern part of Saudi Arabia area has been carried out, for the minimization and mitigation of earthquake losses. The study area...     

A preliminary study on the potential of the geothermal resources around the Gulf of Suez, Egypt

The Gulf of Suez is characterized by the presence of many hot springs and deep thermal wells scattered around its coastal areas. So it is considered one of the promised geothermal areas in Egypt. In this study, the main emphasis is to investigate the geothermal potential around the Gulf of Suez using the available logging and geothermometer datasets. The temperature profiles and well logging data of some hot springs and deep wells around or within the coastal area of the Gulf of Suez are used in this study. The temperature profiles are analyzed and some important thermophysical properties are estimated (geothermal gradient, thermal conductivity, heat flow, and specific heat capacity). Such analysis revealed that a medium to high geothermal gradient (22.0–30°C/Km) is given for the Gulf of Suez as a whole, with some spots of much higher gradient in the order of 35.0–44°C/Km (Ras Fanar and Hammam Faraun areas). The compiled thermal plots show that the thick evaporites and rock salt lithology, which is a major constituent in this area, attain the highest thermal conductivity (>3.10 W/m/K) and heat flow (>90 mW/m²) and the lowest specific heat capacity (<0.30 J/kg/K). The available gamma ray and the natural gamma ray spectroscopy logs are used to conduct a radioactive-based heat generation study using the characteristic radioactive nature of some elements like; ²³⁸U, ²³⁵U, ²³²Th, and of the isotope of ⁴⁰K. A good linearity is observed between the heat production (A in microwatt per cubic meter) and the gamma ray (API) along a wide range of datasets (0–150 API) in all wells. The heat production factor increases in the carbonate lithology (up to 3.20?μW/m³) and is proportional to the shale volume. A geothermometer-based study is used to estimate the subsurface formation temperature and heat flow from the geochemical analysis of some water samples collected from the studied hot springs. The estimated thermal parameters are in harmony with the regional thermal regime concluded form logging data. A thermal basin growth study, in relation to the clay diagenesis is conducted concerning the thermal effects that take place with depth giving rise to another clay mineral (illite). Furthermore, a number of 2D thermal–burial history diagrams are constructed for the complied sections of some of the studied areas to show the vertical distribution of the estimated petrothermal properties. A reserve evaluation study is carried out to estimate the economic geothermal capacity of these hot springs to be used as alternative clean source for possible energy production (electricity) and other low-temperature purposes.     

Decomposition of wind speed fluctuations at different time scales

Understanding the inherent features of wind speed (variability on different time scales) has become critical for assured wind power availability, grid stability, and effective power management. The study utilizes the wavelet, autocorrelation, and FFT (fast Fourier transform) techniques to analyze and assimilate the fluctuating nature of wind speed data collected over a period of 29–42 years at different locations in the Kingdom of Saudi Arabia. The analyses extracted the intrinsic features of wind speed, including the long-term mean wind speed and fluctuations at different time scales (periods), which is critical for meteorological purposes including wind power resource assessment and weather forecasting. The long-term mean wind speed varied between 1.45 m/s at Mecca station and 3.73 m/s at Taif. The annual variation is the largest (±0.97 m/s) at Taif and the smallest (±0.25 m/s) at Mecca. Similarly, the wind speed fluctuation with different periods was also discussed in detail. The spectral characteristics obtained using FFT reveal that Al-Baha, Najran, Taif and Wadi-Al-Dawasser having a sharp peak at a frequency f = 0.00269 (1/day) retain a more regular annual repetition of wind speed than Bisha, Khamis-Mushait, Madinah, Mecca, and Sharourah. Based on the autocorrelation analysis and FFT results, the stations are divided into three groups: (i) having strong annual modulations (Al-Baha, Najran, Taif and Wadi-Al-Dawasser), (ii) having comparable annual and half-yearly modulations (Bisha, Khamis-Mushait, and Mecca) and (iii) having annual modulation moderately prominent (Madinah and Sharourah).     

Reservoir parameters determination using artificial neural networks: Ras Fanar field, Gulf of Suez, Egypt

Ras Fanar field is one of the largest oil-bearing carbonate reservoirs in the Gulf of Suez. The field produces from the Middle Miocene Nullipore carbonate reservoir, which consists mainly of algal-rich dolomite and dolomitic limestone rocks, and range in thickness between 400 and 980 ft. All porosity types within the Nullipore rocks have been modified by diagenetic processes such as dolomitization, leaching, and cementation; hence, the difficulty arise in the accurate determination of certain petrophysical parameters, such as porosity and permeability, using logging data only. In this study, artificial neural networks (ANN) are used to estimate and predict the most important petrophysical parameters of Nullipore reservoir based on well logging data and available core plug analyses. The different petrophysical parameters are first calculated from conventional logging and measured core analyses. It is found that pore spaces are uniform all over the reservoirs (17–23%), while hydrocarbon content constitutes more than 55% and represented mainly by oil with little saturations of secondary gasses. A regular regression analysis is carried out over the calculated and measured parameters, especially porosity and permeability. Fair to good correlation (R <65%) is recognized between both types of datasets. A predictive ANN module is applied using a simple forward backpropagation technique using the information gathered from the conventional and measured analyses. The predicted petrophysical parameters are found to be much more accurate if compared with the parameters calculated from conventional logging analyses. The statistics of the predicted parameters relative to the measured data, show lower sum error (<0.17%) and higher correlation coefficient (R >80%) indicating that good matching and correlation is achieved between the measured and predicted parameters. This well-learned artificial neural network can be further applied as a predictive module in other wells in Ras Fanar field where core data are unavailable.     

Strain Analysis and Microstructural Investigation of the Jabal Tays Ophiolite Complex,Eastern Arabian Shield,Saudi Arabia

Geotectonics - The present study deals with the Jabal Tays ophiolite area, which was affected by Al Amar-Idsas fault. It is one of the most important tectonic features in the Eastern Arabian...     

Hydrocarbon Generation Potential of the Organic-Rich Naifa Formation,Say’un–Masila Rift Basin,Yemen: Insights from Geochemical and Palynofacies Analyses

Natural Resources Research - The Say’un–Masila rift, one of the most important basins of Yemen, contains unconventional resources of organic-rich rocks. In the present work, geochemical...