Abbas, Ahmed K. (Missouri University of science and technology) | Dahm, Haider H. (Misan University) | Flori, Ralph E. (Missouri University of science and technology) | Alsaba, Mortadha (Australian College of Kuwait)
ABSTRACT: Zubair Formation (Lower Cretaceous) is a regionally extended oil-producing sandstone sequence in Iraq, Kuwait, Syria, Iran, and Saudi Arabia. The Zubair oil reservoir has a significant potential to contribute to the petroleum supply in Iraq. The Knowledge of petrophysical and geomechanical properties of the Zubair sandstone formation is required to assure the success of future exploration and development of this reserves. Hence, a high consistency and quality of reservoir properties may significantly improve the economic revenues derivable from the reservoir. This paper presents series of experiments that were conducted to investigate petrophysical and mechanical properties of 40 plug samples retrieved from the Zubair reservoir in Southern Iraq. The measured petrophysical properties included porosity, grain density, bulk density, grain size, and permeability. The geomechanical properties included static and dynamic elastic parameters (Young’s modulus, bulk modulus, shear modulus, and Poisson’s ratio), rock strength parameters (uniaxial compressive strength, cohesion, and internal friction angle), tensile strength, and acoustic velocity (compressional and shear wave velocities). The findings of this study can be used in solving wellbore instability problems, preventing sand production, enhancing reservoir simulation studies, optimizing drilling processes, and designing fracturing operations across the Zubair reservoir.
Zubair sandstone is one of the most important oil reservoirs in Southern Iraq that its petrophysical and geomechanical characters are not well known. These properties play significant role in the exploration and development operations for the hydrocarbon reservoir (Abbas et al., 2018a). In the exploration phase, petrophysical and geomechanical properties are required in pore pressure prediction, hydrocarbon column height estimation, and assessment of fluid flow into wells (Najibi et al., 2017). For the drilling and field development, the geomechanical properties have significant impact on estimating the in-situ stresses in subsurface formations, optimizing the drilling process (selection of the bit type and drilling parameters), optimizing well trajectory placement, casing design, wellbore stability analysis, and development of geomechanical models to address the minimum required mud weight to drill a stable well (Zoback et al., 2003; Alsubaih et al., 2017; Abbas et al., 2018b). Furthermore, unexpected problems such as reservoir compaction and sand production (in sandstone reservoirs) may occur several years after the exploitation and lead to decrease in reservoir pressure and permeability. Subsequently, production rate drop and land subsidence occur in these reservoirs (Khamehchi and Reisi et al., 2015). Thus, it is essential to plan an optimum exploitation of the hydrocarbon resources using petrophysical and geomechanical properties to prevent and/or mitigate the occurrence of these problems. Moreover, hydraulic fracturing techniques while the wells development phase are some remediation activities to enhance oil recovery, which strongly requires the knowledge of petrophysical and geomechanical properties (Wang and Sharma, 2017). Hence, an accurate technique to estimate the petrophysical and geomechanical properties may significantly improve the economic revenues for the Zubair Reservoir. Laboratory tests are the most direct and reliable way of determining petrophysical and geomechanical properties. Typically, geomechanical properties (static properties) can be obtained by gently applying uniaxial or triaxial stresses on cylindrical plug samples until failure occurs.
It is critical to obtain the rock strength along the wellbore to control drilling problems such as pipe sticking, tight hole, collapse and sand production. The purpose of this research is to predict the uniaxial compressive strength based on data of sonic travel time, formation porosity, density and penetration rate. For prediction of UCS, artificial neural networks were developed between UCS and input data resulting a practical correlation. In this research, a long well segment possessing complete and continuous data coverage has been analysed, and collected data of the wellbore are used to correlate data of the four mentioned input parameters of artificial neural networks with uniaxial compressive strength data as network targets. Selection of input parameters is based on a vast literature review in this area. Due to the fact that standard experimental test methods based on established standards require costly equipment and that the methods for sample preparation is difficult and time-consuming, indirect methods are more favourable. Using these methods, the UCS values are predicted in a simpler, faster and more economical way. In this study, it is concluded that artificial neural networks are a good predictor of rock strength, and can reduce drilling costs significantly. It is observed in this paper that UCS predicted values by neural networks are very close with lab and field data, which is concluded by analysis of network performance results including mean squared error and correlation coefficient. It is also concluded in this study that input parameters which are chosen in this study, have deep effects in UCS prediction studies, and should be considered in other scientific studies. Conclusions show that using artificial neural networks to predict UCS of formation rocks in petroleum fields around the world, would ease UCS estimation, optimize drilling plans and decrease costs.
A geomechanical model requires a great deal of input information including measurements of magnitude of vertical and minimum stresses, pore pressure, rock mechanics properties and drilling experiences, all oriented to determine the magnitude of maximum horizontal stress. To conduct a geomechanical reservoir characterization, it is essential to have the knowledge of the in-situ stress magnitudes and rock mechanical properties .
khair, Elham Mohammed M. (Sudan University of Science & Technology) | Zhang, Shicheng (China University of Petroleum, Beijing) | Abdelrahman, Ibrahim Mustafa (Sudan University of Science & Technology)
The current study presents elastic properties model for Fulla Oilfield in northeast of Block 6 in south of Sudan. Due to the poor formation consolidation and relatively viscose fluid, reservoirs may predictably produce massive amounts of sand and numerous troubles were found in the field as a result of sanding. No documented researches were found to introduce good parameters for rock strength and rock failure conditions through the field. Therefore, an accurate technique for predicting rock failure conditions may yield good profits and improve the economic returns through preventing sand production from the formations. General correlations were presented to accurately describe rock strength parameters for the field; the work utilizes the application of the wireline porosities to be used as a strength indicator through the combination of rock mechanical theories with the characterization of Fulla oilfield. Log porosities (density, sonic and neutron) were calibrated with the core measured porosity, and the best matching porosity were correlated with the dynamic calibrated strength parameters by different correlations. The results support the evidence of the use of porosity as an index for mechanical properties; power functions were found more reliable than the exponential functions, and can be used with a high degree of confidence; also it is more accurate than the Shale Index model presented in previous work for same field; however, the result does not support the direct linear expression presented in the literature for other field due to the variations in the field conditions.