scholarly journals The assessment of rock drillability from elastic and petrophysical parameters

2022 ◽  
Vol 11 (1) ◽  
pp. 48-57
Author(s):  
Mostafa A. Teama ◽  
Mohamed A. Kassab ◽  
Moataz M. Gomaa ◽  
Abdelrahman B. Moussa
2012 ◽  
Vol 57 (2) ◽  
pp. 363-373
Author(s):  
Jan Macuda

Abstract In Poland all lignite mines are dewatered with the use of large-diameter wells. Drilling of such wells is inefficient owing to the presence of loose Quaternary and Tertiary material and considerable dewatering of rock mass within the open pit area. Difficult geological conditions significantly elongate the time in which large-diameter dewatering wells are drilled, and various drilling complications and break-downs related to the caving may occur. Obtaining higher drilling rates in large-diameter wells can be achieved only when new cutter bits designs are worked out and rock drillability tests performed for optimum mechanical parameters of drilling technology. Those tests were performed for a bit ø 1.16 m in separated macroscopically homogeneous layers of similar drillability. Depending on the designed thickness of the drilled layer, there were determined measurement sections from 0.2 to 1.0 m long, and each of the sections was drilled at constant rotary speed and weight on bit values. Prior to drillability tests, accounting for the technical characteristic of the rig and strength of the string and the cutter bit, there were established limitations for mechanical parameters of drilling technology: P ∈ (Pmin; Pmax) n ∈ (nmin; nmax) where: Pmin; Pmax - lowest and highest values of weight on bit, nmin; nmax - lowest and highest values of rotary speed of bit, For finding the dependence of the rate of penetration on weight on bit and rotary speed of bit various regression models have been analyzed. The most satisfactory results were obtained for the exponential model illustrating the influence of weight on bit and rotary speed of bit on drilling rate. The regression coefficients and statistical parameters prove the good fit of the model to measurement data, presented in tables 4-6. The average drilling rate for a cutter bit with profiled wings has been described with the form: Vśr= Z ·Pa· nb where: Vśr- average drilling rate, Z - drillability coefficient, P - weight on bit, n - rotary speed of bit, a - coefficient of influence of weight on bit on drilling rate, b - coefficient of influence of rotary speed of bit on drilling rate. Industrial tests were performed for assessing the efficiency of drilling of large-diameter wells with a cutter bit having profiled wings ø 1.16 m according to elaborated model of average rate of drilling. The obtained values of average rate of drilling during industrial tests ranged from 8.33×10-4 to 1.94×10-3 m/s and were higher than the ones obtained so far, i.e. from 181.21 to 262.11%.


2021 ◽  
Author(s):  
Ping Zhang ◽  
◽  
Wael Abdallah ◽  
Gong Li Wang ◽  
Shouxiang Mark Ma ◽  
...  

It is desirable to evaluate the possibility of developing a deeper dielectric permittivity based Sw measurement for various petrophysical applications. The low frequency, (< MHz), resistivity-based method for water saturation (Sw) evaluation is the desired method in the industry due to its deepest depth of investigation (DOI, up to 8 ft). However, the method suffers from higher uncertainty when formation water is very fresh or has mixed salinity. Dielectric permittivity and conductivity dispersion have been used to estimate Sw and salinity. The current dielectric dispersion tools, however, have very shallow DOI due to their high measurement frequency up to GHz, which most likely confines the measurements within the near wellbore mud-filtrate invaded zones. In this study, effective medium-model simulations were conducted to study different electromagnetic (EM) induced-polarization effects and their relationships to rock petrophysical properties. Special attention is placed on the complex conductivity at 2 MHz due to its availability in current logging tools. It is known that the complex dielectric saturation interpretation at the MHz range is quite difficult due to lack of fully understood of physics principles on complex dielectric responses, especially when only single frequency signal is used. Therefore, our study is focused on selected key parameters: water-filled porosity, salinity, and grain shape, and their effects on the modeled formation conductivity and permittivity. To simulate field logs, some of the petrophysical parameters mentioned above are generated randomly within expected ranges. Formation conductivity and permittivity are then calculated using our petrophysical model. The calculated results are then mixed with random noises of 10% to make them more realistic like downhole logs. The synthetic conductivity and permittivity logs are used as inputs in a neural network application to explore possible correlations with water-filled porosity. It is found that while the conductivity and permittivity logs are generated from randomly selected petrophysical parameters, they are highly correlated with water-filled porosity. Furthermore, if new conductivity and permittivity logs are generated with different petrophysical parameters, the correlations defined before can be used to predict water-filled porosity in the new datasets. We also found that for freshwater environments, the conductivity has much lower correlation with water-filled porosity than the one derived from the permittivity. However, the correlations are always improved when both conductivity and permittivity were used. This exercise serves as proof of concept, which opens an opportunity for field data applications. Field logs confirm the findings in the model simulations. Two propagation resistivity logs measured at 2 MHz are processed to calculate formation conductivity and permittivity. Using independently estimated water-filled porosity, a model was trained using a neural network for one of the logs. Excellent correlation between formation conductivity and permittivity and water-filled porosity is observed for the trained model. This neural network- generated model can be used to predict water content from other logs collected from different wells with a coefficient of correlation up to 96%. Best practices are provided on the performance of using conductivity and permittivity to predict water-filled porosity. These include how to effectively train the neural network correlation models, general applications of the trained model for logs from different fields. With the established methodology, deep dielectric-based water saturation in freshwater and mixed salinity environments is obtained for enhanced formation evaluation, well placement, and reservoir saturation monitoring.


SPE Journal ◽  
2021 ◽  
pp. 1-20
Author(s):  
Shouxiang Mark Ma ◽  
Gabriela Singer ◽  
Songhua Chen ◽  
Mahmoud Eid

Summary Typically, smooth solid surfaces of reservoir rocks are assumed in formation evaluation, such as nuclear-magnetic-resonance (NMR) petrophysics and reservoir-wettability characterization through contact-angle measurements. Measuring the degree of surface roughness (R), or smoothness, and evaluating its effects on formation evaluation are topics of much research. In this paper, we primarily focus on details in characterizing solid-surface roughness and its applications in NMR pore-sizeanalysis. R can be measured by contact techniques and noncontact techniques, such as stylus profilometer, atomic-force microscopy, and different kinds of optical measurements. Each technique has different sensitivities, measurement artifacts, resolutions, and field of view (FOV). Intuitively, although a finer resolution measurement provides the closest account of all surface details, the correspondingly small FOV might compromise the representativeness of the measurement, which is particularly challenging for charactering heterogeneous samples such as carbonates. To balance the FOV and measurement representativeness, and to minimize artifacts, laser scanner confocal microscopy (LSCM) is selected in this study. Results for the more than 27 rock samples tested indicate that rocks of similar rock types have similar R-values. Grainy limestones have relatively higher R-values compared with dolostones, consistent with the dolostone’s crystallization surface features. Muddy limestones have smoother surfaces, resulting in the lowest R-values among the rocks studied. For sandstones, R varies with clay types and content. For rocks containing two distinct minerals, two R-values are observed from the R profiles, which for these rock types justifies the use of two NMR surface relaxivity (ρ2) parameters for determining the pore-size distribution (PSD) from the NMR T2distribution. The novelty here is the integration of LSCM and NMR to obtain an NMR PSD relevant for permeability, capillary pressure, and other petrophysical parameters. Typically, ρ2 is calibrated using the total surface area from Brunauer-Emmett-Teller (BET; Brunauer et al. 1938) gas adsorption, but this underestimates the NMR pore size because of surface-roughness effects. In our novel approach, we use R measured from LSCM to correct ρ2 for surface-roughness effects, and thereby obtain the NMR pore size more relevant for permeability and other petrophysical parameters. We then compare the roughness-corrected NMR PSD against pore size from microcomputed tomography (micro-CT) scanning (which is roughness independent). The good agreement between roughness-corrected NMR and micro-CT pore sizes in the micropore region validates our new technique, and highlights the importance of surface-roughness characterization in NMR petrophysics.


2017 ◽  
Vol 5 (1) ◽  
pp. 19
Author(s):  
Ubong Essien ◽  
Akaninyene Akankpo ◽  
Okechukwu Agbasi

Petrophysical analysis was performed in two wells in the Niger Delta Region, Nigeria. This study is aimed at making available petrophysical data, basically water saturation calculation using cementation values of 2.0 for the reservoir formations of two wells in the Niger delta basin. A suite of geophysical open hole logs namely Gamma ray; Resistivity, Sonic, Caliper and Density were used to determine petrophysical parameters. The parameters determined are; volume of shale, porosity, water saturation, irreducible water saturation and bulk volume of water. The thickness of the reservoir varies between 127ft and 1620ft. Average porosity values vary between 0.061 and 0.600; generally decreasing with depth. The mean average computed values for the Petrophysical parameters for the reservoirs are: Bulk Volume of Water, 0.070 to 0.175; Apparent Water Resistivity, 0.239 to 7.969; Water Saturation, 0.229 to 0.749; Irreducible Water Saturation, 0.229 to 0.882 and Volume of Shale, 0.045 to 0.355. The findings will also enhance the proper characterization of the reservoir sands.


2020 ◽  
Author(s):  
Sudad H Al-Obaidi

Practical value of this work consists in increasing the efficiency of exploration for oil and gas fields in Eastern Baghdad by optimizing and reducing the complex of well logging, coring, sampling and well testing of the formation beds and computerizing the data of interpretation to ensure the required accuracy and reliability of the determination of petrophysical parameters that will clarify and increase proven reserves of hydrocarbon fields in Eastern Baghdad. In order to calculate the most accurate water saturation values for each interval of Zubair formation, a specific modified form of Archie equation corresponding to this formation was developed.


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