Gas Deviation Factor Calculation Made Easy and Accurate Using an IR 4.0 Tool

Gas deviation factor (z-factor) and other gas reservoir fluid properties, such as formation volume factor, density, and viscosity, are normally obtained from Pressure-Volume-Temperature (PVT) experimental analysis. This process of reservoir fluid characterization usually requires collecting pressurized fluid samples from the wellbore to conduct the experimental work. The scope of this paper will provide an alternative methodology for obtaining the z-factor. An IR 4.0 tool that heavily utilizes software coding was developed. The advanced tool uses the novel apparent molecular weight profiling concept to achieve the paper objective timely and accurately. The developed tool calculates gas properties based on downhole gradient pressure and temperature data as inputs. The methodology is applicable to dry, wet or condensate gas wells. The gas equation of state is modified to solve numerically for the z-factor using the gradient survey pressure and temperature data. The numerical solution is obtained by applying an iterative computation scheme as described below:A gas apparent molecular weight value is initialized and then gas mixture specific gravity and pseudo-critical properties are calculated.Gas mixture pseudo-reduced properties are calculated from the measured pressure and temperature values at the reservoir depth.A first z-factor value is determined as a function of the pseudo-reduced gas properties.Gas pressure gradient is obtained at the reservoir depth from the survey and used to back-calculate a second z-factor value by applying the modified gas equation of state.Relative error between the two z factor values is then calculated and compared against a low predefined tolerance.The above steps are reiterated at different assumed gas apparent molecular weight values until the predefined tolerance is achieved. This numerical approach is computerized to perform the highest possible number of iterations and then select the z-factor value corresponding to the minimum error among all iterations. The proposed workflow has been applied on literature data with known reservoir gas properties, from PVT analysis, and showed an excellent prediction performance compared to laboratory analysis with less than 5% error.

Validation of The Cullender and Smith Method for Determining Pressure Loss in The Tubing in Gas Wells

The ability of the reservoir to deliver a certain quantity of gas depends both on the inflow performance relationship and the flowing bottom hole pressure. In order to determine the deliverability of the total well system, it is necessary to calculate all the parameters and pressure drops, one of which in the tubing. Calculation of pressure loss in the tubing is a very important parameter in the stability of fluid flow from the reservoir to the surface. The calculation of pressure loss in the tubing which is most widely used in the field is the Cullender and Smith Method. The purpose of this study is to validate why the Cullender and Smith method is most widely used in the field to determine the pressure loss in the tubing compared to other pressure loss in tubing methods. The methodology used in this study is calculating the pressure loss in the tubing with the Average Temperature and Deviation Factor Method, the Sukkar and Cornel Method, and the Cullender and Smith Method. After calculating the pressure loss in the tubing using each of these methods, then comparing the percent error of the calculation method with the results in the well. The data used in the calculation is the data from the MZ Field from 7 wells in the East Kalimantan area. The results of the average error percentage obtained from this study are the Average and Deviation Factor Method is 5.38%, the Sukkar and Cornell Method is 5.65%, and the Cullender and Smith Method is 3.83%. From this study, it can be said that the Cullender and Smith Method to be valid or the most accurate method for used in the field compared to other methods due to resulting the smallest percent error from the calculation.

A Study to Establish Correlation Between Rebound Value and Compressive Strength of Concrete Using Materials Available Locally in Nagpur

This study has been taken to investigate the exact rebound-strength relationship of different grades of concrete, as the curves generated for traditional hammers are outdated. Using the material available in the Nagpur region, cube specimens were cast and tested as per IS:516-1959 [1]. Several sets were cast with varying cement contents, decided by mix design, to give a strength range of 10 to 50 Mpa. However, for this study, the Target Mean Strength Standard Deviation factor is not considered. We tested these sets for compressive strengths; each specimen was checked for rebound value for compressive Strength, each specimen was checked for rebound value on four faces. Thus, for each specimen, data for rebound value and Compressive Strength is available. Using this data, a curve for Compressive Strength and rebound value was plotted. The curve generated indicated that the strengths obtained for the same rebound value are higher than that using the traditional curve. There is an increase of about 47% up to a strength of 21 Mpa. From 21 to 38 Mpa, this increase is almost constant to about 30%. From this point forward, the rate of increased Strength reduces by 25% and 14% at 40 Mpa and 45 Mpa, respectively.

A Comprehensive Review of Recent Advances in the Estimation of Natural Gas Compressibility Factor

Accurate prediction of gas compressibility factor is essential for the evaluation of gas reserves, custody transfer and design of surface equipment. Gas compressibility factor (Z) also known as gas deviation factor can be evaluated by experimental measurement, equation of state and empirical correlation. However, these methods have been known to be expensive, complex and of limited accuracy owing to the varying operating conditions and the presence of non-hydrocarbon components in the gas stream. Recently, newer correlations with extensive application over wider range of operating conditions and crude mixtures have been developed. Also, artificial intelligence is now being deployed in the evaluation of gas compressibility factor. There is therefore a need for a holistic understanding of gas compressibility factor vis-a-vis the cause-effect relations of deviation. This paper presents a critical review of current understanding and recent efforts in the estimation of gas deviation factor.

Investigation of the Strength Parameters of Drilling Pumps during the Formation of Contact Stresses in Gears

The relevance of this research lies in the need to develop scientifically based methods for calculating and designing a transmission shaft with a hardened coating of increased strength and service life of a core drilling pump drive that can allow for a redistributing of resistance forces along the contact surfaces of the gear. This relevance is confirmed by the need to improve domestic methods for designing drive shafts of increased reliability which can ensure the development of frozen soils during deposits exploration. The purpose of the research is to increase the energy efficiency and service life of the high-loaded drive gear teeth of core drilling pump transmission shafts by justifying the critical loads and stresses in hardened gear coatings acting under intense wear of the contact surface with a broken contact symmetry. The criteria for the effective wear area with an uneven contact cross-section at the maximum bending moments of the transmission shaft of the drilling pump were justified and presented in the work. Additionally, the process of interaction of the transmission shaft gear teeth with the eccentric shaft gear at uneven axial torques was investigated. The effective power (Ng) of the gearing of the drive transmission shaft gear and the eccentric shaft gear, which characterizes the energy consumption of the drill bit depth stroke, was justified. This work also proposes a method of substantiating the technological and power parameters of the transmission shaft by using Legendre polynomials. A nomographic chart was developed for the determination of the dependence of the contact stress base cycles on the change in the load distribution factor and the contact spot deviation factor from the design axis λ.

A Novel Simplification for the Prediction of Natural Gas Compressibility Factor

The need for a simpler, effective and less expensive predictive tool for the estimation of natural gas compressibility factor cannot be exaggerated. An accurate prediction of gas compressibility factor is essential because it plays a definitive role in evaluating gas reservoir properties used in the estimation of gas reserves, custody transfer and design of surface equipment. In this present work, a novel explicit correlation and a highly sophisticated computer program were developed to accurately predict natural gas deviation factor. The research also aims to effectively capture the relationship between Pseudo-reduced temperature and pressure in relations to the Z-factor. In this study, 3972 digitized data points extracted from Standing and Katz’s Chart were regressed and analyzed using Microsoft Excel Spreadsheet, the extraction of this data was done using WebPlotDigitizer developed by Ankit Rohatgi of GitHub, Pacifica, CA, USA. The correlation was developed as a function of Pseudo-reduced temperature and pressure with tuned parameters distributed across 1.05 ≤ Tpr ≤ 3.0 and 0 < Ppr ≤ 8.0. Subsequently, the input (Tpr and Ppr values) of the feed data was used to validate the correlation and compare it with other known and published correlations. Statistical analysis of the results showed that a 99.8% agreement exists between the predicted and actual compressibility factors for the various test scenarios and case studies involving both sweet and sour gases. Also, the correlation was observed to outperform other models. Finally, the results were observed to perfectly mimic the Standing and Katz charts with an overall correlation coefficient of 99.76% and an adjusted R2 of 99.75%. The proposed correlation was subsequently used to develop a software using JavaScript. Undoubtedly, the proposed correlation and software are suitable for rapid and accurate simplification and prediction of natural gas compressibility factor.

Reserve Estimation from Early Time Production Data in Geopressured Gas Reservoir: Gas Production of Cumulative Unit Pressure Drop Method

There is high uncertainty in reserve estimation during the early development of deep ultrahigh pressure gas reservoirs, largely because it remains challenging in accurately determining the formation compressibility. To overcome this, starting from the definition of compressibility, a novel gas production of cumulative unit pressure drop analysis method was established, of which the effectiveness was proven by applications in calculating the reserves of three gas reservoirs. It has been found that, in the limiting case, i.e., when the formation pressure dropped to the normal atmospheric pressure, the dimensionless gas production of the cumulative unit pressure drop was the reciprocal of the initial formation pressure. Besides, the relationship curve of the dimensionless gas production of the cumulative unit pressure drop and pressure drop was a straight line in the medium term, extending the straight line and intersecting the vertical line passing through the original formation pressure point, and the reserves can be determined according to the intersection point and the initial formation pressure. However, due to the influence of natural gas properties, the value needs further correction, and the correction coefficient depends on the pseudocritical temperature of natural gas. Specifically, when the pseudocritical temperature is given, the correction coefficient would be close to the minimum value of the natural gas deviation factor. When the pseudocritical temperature is more than 1.9 and less than 3.0, the minimum deviation factor would be between 0.90 and 1.0, and the higher the pseudocritical temperature, the closer the ratio is to 1.0.

Development of a Simpler but Accurate Free Gas Deviation Factor for Fractured (Dual-Porosity) Volumetric Gas Reservoir Fluid

Gas compressibility factor, also known as gas deviation factor or Z-factor, is a thermodynamic correction factor which describes the deviation of a real gas from ideal gas behaviour. The, free gas Z-factor in the Material Balance Equation (MBE) of single-porosity gas reservoirs with insignificant rock (matrix) compaction (after pressure depletion) does not reflect cases in low-permeability gas reservoirs having remarkable rock compaction. Through gas MBE modifications, previous researchers developed Z-factors for dual-porosity (fractured) low permeability gas reservoirs by incorporating gas desorption; however, their approaches create complexity for routine calculations. Therefore this study was designed with the purpose of deriving a free gas Z-factor for single-porosity low-permeability gas reservoirs and further modifying it for more simplicity and accuracy in a dual-porosity scenario. The free gas Z-factor derived for single-porosity low-permeability gas reservoirs is expressed as: where , , , , and are single-porosity Z-factor without rock compaction at pressure , water compressibility, initial water saturation, matrix compressibility, initial gas saturation and pressure depletion, respectively. However, the developed dual porosity free gas Z-factor model incorporates ratio of dual porosity to initial matrix porosity, and it is expressed as: where and are initial matrix porosity and fracture porosity, respectively. The Z-factor model was graphically and statistically correlated with an existing free gas Z-factor model for dual porosity reservoirs. For all the hydraulically fractured shale gas formations considered, the correlations yield R2 values of 1.000.

An insight into the estimation of drilling fluid density at HPHT condition using PSO-, ICA-, and GA-LSSVM strategies

The present study evaluates the drilling fluid density of oil fields at enhanced temperatures and pressures. The main objective of this work is to introduce a set of modeling and experimental techniques for forecasting the drilling fluid density via various intelligent models. Three models were assessed, including PSO-LSSVM, ICA-LSSVM, and GA-LSSVM. The PSO-LSSVM technique outperformed the other models in light of the smallest deviation factor, reflecting the responses of the largest accuracy. The experimental and modeled regression diagrams of the coefficient of determination (R2) were plotted. In the GA-LSSVM approach, R2 was calculated to be 0.998, 0.996 and 0.996 for the training, testing and validation datasets, respectively. R2 was obtained to be 0.999, 0.999 and 0.998 for the training, testing and validation datasets, respectively, in the ICA-LSSVM approach. Finally, it was found to be 0.999, 0.999 and 0.999 for the training, testing and validation datasets in the PSO-LSSVM method, respectively. In addition, a sensitivity analysis was performed to explore the impacts of several variables. It was observed that the initial density had the largest impact on the drilling fluid density, yielding a 0.98 relevancy factor.