scholarly journals Application of a new approach for modeling the oil field formation damage due to mineral scaling

2019 ◽  
Vol 74 ◽  
pp. 62 ◽  
Author(s):  
Alireza Rostami ◽  
Amin Shokrollahi ◽  
Khalil Shahbazi ◽  
Mohammad Hossein Ghazanfari
Keyword(s):  
Sea Water ◽  
Gene Expression Programming ◽  
Oil Field ◽  
Superior Performance ◽  
Formation Damage ◽  
Mixed Salt ◽  
Statistical Parameters ◽  
Sulfate Salt ◽  
Salt Deposition ◽  
Mineral Scaling

Mineral scaling has been considered a great concern for developing the oil production from the underground petroleum reservoirs. One of the main causes of this phenomenon is known as the chemical incompatibility of injected brine, frequently sea water, with the reservoir brine leading to the deposition of various supersaturated salts such as calcium carbonate, calcium sulfate and barium sulfate. In present communication, an evolutionary approach namely, Gene Expression Programming (GEP), was employed for rigorous modeling of formation damage by mineral scaling of mixed sulfate salt deposition. At first, a large databank of damaged permeability datapoints as a function of injected volume, injection flowrate, temperature, differential pressure and ionic concentrations of the existing chemical species in the porous media was employed. In this regard, a user-friendly correlation was extended for the first time by the aforementioned technique in the literature. Professional evaluation of the suggested GEP-based model was implemented by different statistical parameters and appealing visualization tools. Having proposed the GEP-based correlation, statistical parameters of the Average Absolute Relative Deviation Percent (AARD%) of 0.640% and determination coefficient (R2) of 0.984 was calculated. Accordingly, it is demonstrated that the proposed model has a superior performance and great potential for efficient prediction of damaged permeability due to the mixed sulfate salt scaling. Moreover, the implemented outlier diagnosis technique verified the validity of the databank used for modeling, as well as the high robustness of the suggested model was confirmed. In conclusion, the developed correlation in this work can be of enormous practical value for skillful engineers and scientists in any academic study and industrial applications dealing with mixed salt deposition.

scholarly journals Constitutive Models for the Prediction of the Hot Deformation Behavior of the 10%Cr Steel Alloy

Materials ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 2873 ◽  
Author(s):  
Abdallah Shokry ◽  
Samer Gowid ◽  
Ghias Kharmanda ◽  
Elsadig Mahdi
Keyword(s):  
Relative Error ◽  
Hot Deformation ◽  
Mean Squared Error ◽  
Flow Behavior ◽  
Constitutive Models ◽  
Superior Performance ◽  
Steel Alloy ◽  
Statistical Parameters ◽  
Average Absolute Relative Error ◽  
Ann Models

The aim of this paper is to establish a reliable model that provides the best fit to the specific behavior of the flow stresses of the 10%Cr steel alloy at the time of hot deformation. Modified Johnson–Cook and strain-compensated Arrhenius-type (phenomenological models), in addition to two Artificial Neural Network (ANN) models were established with the view toward investigating their stress prediction performances. The ANN models were trained using Scaled Conjugate Gradient (SCG) and Levenberg–Marquardt (LM) algorithms. The prediction accuracy of the established models was evaluated using the following well-known statistical parameters: (a) correlation coefficient (R), (b) Average Absolute Relative Error (AARE), (c) Root Mean Squared Error (RMSE), and Relative Error (RE). The results showed that both of the modified Johnson–Cook and strain-compensated Arrhenius models could not competently predict the flow behavior. On the contrary, the results indicated that the two proposed ANN models precisely predicted the flow stress values and that the LM-trained ANN provided a superior performance over the SCG-trained model, as it yielded an RMSE of as low as 0.441 MPa.

Solubility Of Common Oil Field Scales Of Injection Water And High–barium Concentration And High–salinity Formation Water

2012 ◽  
Author(s):  
Amer Badr Merdhah ◽  
Abu Azam Mohd Yassin
Keyword(s):  
Oil And Gas ◽  
High Salinity ◽  
Sea Water ◽  
Water Injection ◽  
Gas Production ◽  
Oil Field ◽  
Formation Water ◽  
Oil And Gas Production ◽  
Barium Concentration ◽  
Injection Water

Kerak pemendapan merupakan satu daripada masalah paling penting dan serius dalam sistem suntikan air. Kerak kadangkala mengehadkan atau menghalang penghasilan gas dan minyak melalui penyumbatan matrik atau perpecahan pembentukan minyak dan jeda yang berlubang. Makalah ini mengetengahkan kesimpulan pengukuran makmal bagi kerak terbentuk di dalam keterlarutan medan minyak biasa dalam sintetik air masin (pembentukan air dan air laut) bagi pembentukan air yang mengandungi barium dan kandungan garam yang tinggi pada suhu 40 hingga 90°C pada tekanan atmosfera. Keputusan uji kaji mengesahkan pola kebergantungan keterlarutan bagi kerak medan minyak biasa pada keadaan ini. Pada suhu yang lebih tinggi, kerak bagi CaCO3, CaSO4, dan SrSO4 meningkat manakala kerak BaSO4 menurun disebabkan oleh keterlarutan CaCO3, CaSO4, dan SrSO4 menurun dan keterlarutan BaSO4 meningkat dengan kenaikan suhu. Kata kunci: Masalah pengskalaan; skala keterlarutan; paras kandungan garam tinggi; logam barium tinggi Scale deposition is one of the most important and serious problems which water injection systems are generally engaged in. Scale sometimes limits or blocks oil and gas production by plugging the oil–producing formation matrix or fractures and the perforated intervals. This paper presents a summary of the laboratory measurements of the solubility of common oil field scales in synthetic brines (formation water and sea water) of high–barium and high–salinity formation waters at 40 to 90°C and atmospheric pressure. The experimental results confirm the general trend in solubility dependencies for common oil field scales at these conditions. At higher temperatures the deposition of CaCO3, CaSO4 and SrSO4 scale increases and the deposition of BaSO4 scale decreases since the solubilities of CaCO3, CaSO4 and SrSO4 scales decreases and the solubility of BaSO4 increases with increasing temperature. Key words: Scaling problems; solubility of scale; high salinity; high barium

scholarly journals Rheological properties of emulsion of crude oil and water

1999 ◽  
Vol 21 (4) ◽  
pp. 213-230
Author(s):  
Duong Ngoc Hai ◽  
Nguyen Van Diep ◽  
Ha Ngoc Hien ◽  
Nguyen The Duc ◽  
Phung Dinh Thuc ◽  
...  
Keyword(s):  
Crude Oil ◽  
Rheological Properties ◽  
Sea Water ◽  
Water Concentration ◽  
Analytical Approximation ◽  
Oil Field ◽  
Wide Range ◽  
Measurement Results ◽  
Effective Dynamic ◽  
White Tiger

In the paper the rheological properties of crude oil of White Tiger oil-field (Vietnam) and its emulsion with sea-water, including measurement results and analytical approximation formulae for wide range of pressure, temperature and water concentration, are presented. As it is known, the crude oil of White Tiger oil-field is a high-paraffin and high-viscous oil. At the low temperature (T ≤ 40°C) it behaves as non-Newtonian fluid of Bingham-Shvedov group. Therefore, beside the effective viscosity, the effective dynamic shear stress is also measured and approximated. The rheological properties of crude oil and emulsion of crude oil and water are also measured and approximated for the case when the mixture contains 0.1% chemical reagent ES-3363.

scholarly journals Gene-Expression Programming-Based Model for Estimating the Compressive Strength of Cement-Fly Ash Stabilized Soil and Parametric Study

2021 ◽  
Vol 6 (12) ◽  
pp. 181
Author(s):  
Van-Ngoc Pham ◽  
Erwin Oh ◽  
Dominic E. L. Ong
Keyword(s):  
Gene Expression ◽  
Compressive Strength ◽  
Fly Ash ◽  
Calcium Oxide ◽  
Parametric Study ◽  
Soil Stabilization ◽  
Gene Expression Programming ◽  
Superior Performance ◽  
Stabilized Soil ◽  
Research Findings

The study aims to develop a reliable model using gene-expression programming (GEP) technique for estimating the unconfined compressive strength (UCS) of soil stabilization by cement and fly ash. The model considered the effects of several parameters, including the fly ash characteristics such as calcium oxide (CaO) content, CaO/SiO2 ratio, and loss of ignition. The research results show that the proposed model demonstrates superior performance with a high correlation coefficient (R > 0.955) and low errors. Therefore, the model could be confidently applied in practice for a variety of fly ash qualities. Besides, the parametric study was conducted to examine the effect of fly ash characteristics on the strength of soil stabilization. The study indicates that if the fly ash contains a high amount of calcium oxide, the strength of fly ash stabilized soil is significant. In addition, fly ash could be used in combination with cement to increase the strength of the mixture. A fly ash replacement ratio is suggested from 0.19 to 0.35, corresponding to the total binder used from 10% to 30%. The research findings could help engineers in optimizing the fly ash proportion and estimating the UCS of soil stabilization by cement and fly ash.

scholarly journals Prediction of the depth of local scouring at a bridge pier using a gene expression programming method

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Waqed H. Hassan ◽  
Halah K. Jalal
Keyword(s):  
Gene Expression ◽  
Mean Squared Error ◽  
Human Life ◽  
Gene Expression Programming ◽  
Absolute Error ◽  
Width Ratio ◽  
Statistical Parameters ◽  
Data Set ◽  
Total Data ◽  
Local Depth

AbstractLocal scouring around the piers of a bridge is the one of the major reasons for bridge failure, potentially resulting in heavy losses in terms of both the economy and human life. Prediction of accurate depth of local scouring is a difficult task due to the many factors that contribute to this process, however. The main aim of this study is thus to offer a new formula for the prediction the local depth of scouring around the pier of a bridge using a modern fine computing modelling technique known as gene expression programming (GEP), with data obtained from numerical simulations used to compare GEP performance with that of a standard non-linear regression (NLR) model. The best technique for prediction of the local scouring depth is then determined based on three statistical parameters: the determination coefficient (R2), mean absolute error (MAE), and root mean squared error (RMSE). A total data set of 243 measurements, obtained by numerical simulation in Flow-3D, for intensity of flow, ratio of pier width, ratio of flow depth, pier Froude number, and pier shape factor is divided into training and validation (testing) datasets to achieve this. The results suggest that the formula from the GEP model provides better performance for predicting the local depth of scouring as compared with conventional regression with the NLR model, with R2 = 0.901, MAE = 0.111, and RMSE = 0.142. The sensitivity analysis results further suggest that the ratio of the depth of flow has the greatest impact on the prediction of local scour depth as compared to the other input parameters. The formula obtained from the GEP model gives the best predictor of depth of scouring, and, in addition, GEP offers the special feature of providing both explicit and compressed arithmetical terms to allow calculation of such depth of scouring.

Leveraging a New Well Delivery Methodology for Stellar Drilling Results Steam Injection Project Case Study

2021 ◽  
Author(s):  
Carlos Alejandro Terrones Brand ◽  
Miguel Alejandro Basso Mora ◽  
Rajeswary Kandasamy ◽  
Sergio Comarin ◽  
Felipe Rene Bustos Guevara ◽  
...  
Keyword(s):  
Performance Monitoring ◽  
New Technologies ◽  
Service Providers ◽  
Oil Production ◽  
Steam Injection ◽  
Gas Production ◽  
Oil Field ◽  
Superior Performance ◽  
Stringent Performance

Abstract Mexico has set challenging oil and gas production to meet worldwide demand. In order to deliver promised oil production outputs in this challenging environment, the operator came up with efficient partnerships with key service providers to leverage resources and technical know-how whilst encouraging knowledge transfer and drilling project cost reduction. By working with various service companies, the operator creates a competitive environment where each strives to outperform the other. One such success case is in the "S" field, a heavy oil field producing via steam injection in the South of Mexico. Utilizing a creative design and execution methodology, the "S" project team succeeded to deliver improved project performance over the course of drilling the 14 wells in the campaign. The average well operational time was successfully reduced by 10%, hence maximizing the well construction index to 122 m/day and reducing overall well costs. The main strategy to optimize performance is to re-engineer solutions for profitability such as performing a study to replace OBM by WBM, designing a new wellhead system, collaborating with the rig contractor to reduce flat time activities, redesigning cement properties for losses mitigation, improvement of ROP by merging new technologies and local practices, among others. Complementary to this, the strategy is to prioritize realistic areas of improvement by the development and utilization of a new tool called Best of the Best (BoB), a methodology breaking down all well activities in order to measure its fastest time per well and then aiming to achieve that aggressive goal. Detailed follow up in the field allows to reduce operational times by allowing the wellsite team monitor and suggest new and improved ways of doing a routine task all of which result in lower costs per foot. Utilizing this BoB approach and stringent performance monitoring while drilling (pre-actual-post) activity analysis, allowed superior performance to be achieved. The project reached a 60% improvement on well times from the first well drilled to the best performing well. The best well was drilled in 8.68 days versus a field average of 18 days (217 m/day construction index). This generated 369,000 bbls of earlier oil production, 176 days ahead vs client expectations. Furthermore, in coordination with field staff, lessons learned were captured. But this is not enough since fast and effective communication is required, and the BoB methodology provides the solution to share optimization tricks quickly and effectively between crews, to continue well to well improvement and overall project and field level learning. Improved well delivery results is possible only by aligning the detailed planning and execution follow up in both the wellsite and a remote operations centre which monitored drilling activity in real time from town. This synergy and proactive communication system is also a key factor in the project delivery. This paper will present the results from the first application of the ‘Best of Best' (BoB) methodology in Mexico. This successful application enforces the idea that by coupling re-engineering practices to develop a more creative well design along with stringent performance monitoring; any field performance can be improved to deliver stellar results.

Model study on the kinetics of oil field formation damage due to salt precipitation from injection

2004 ◽  
Vol 43 (3-4) ◽  
pp. 201-217 ◽  
Author(s):  
J. Moghadasi ◽  
H. Müller-Steinhagen ◽  
M. Jamialahmadi ◽  
A. Sharif
Keyword(s):  
Oil Field ◽  
Formation Damage ◽  
Salt Precipitation ◽  
Model Study ◽  
Field Formation ◽  
Kinetics Of

scholarly journals Simulation of Turbulent Flow around a Generic High-Speed Train Using Hybrid Models of RANS Numerical Method with Machine Learning

2019 ◽  
Author(s):  
Alireza Hajipour ◽  
Arash Mirabdolah Lavasani ◽  
Mohammad Eftekhari Yazdi ◽  
Amir Mosavi ◽  
Shahaboddin Shamshirband ◽  
...  
Keyword(s):  
Turbulent Flow ◽  
Wind Direction ◽  
High Speed ◽  
Gene Expression Programming ◽  
Pressure Coefficient ◽  
Gaussian Process Regression ◽  
Navier Stokes ◽  
Stream Velocity ◽  
High Speed Train ◽  
Statistical Parameters

In the present paper, an aerodynamic investigation of a high-speed train is performed. In the first section of this article, a generic high-speed train against a turbulent flow is simulated, numerically. The Reynolds-Averaged Navier-Stokes (RANS) equations combined with the SST turbulence model are applied to solve incompressible turbulent flow around a high-speed train. Flow structure, velocity and pressure contours and streamlines at some typical wind directions are the most important results of this simulation. The maximum and minimum values are specified and discussed. Also, the pressure coefficient for some critical points on the train surface is evaluated. In the following, the wind direction influence the aerodynamic key parameters as drag, lift, and side forces at the mentioned wind directions are analyzed and compared. Moreover, the effects of velocity changes (50, 60, 70, 80 and 90 m/s) are estimated and compared on the above flow and aerodynamic parameters. In the second section of the paper, various data-driven methods including Gene Expression Programming (GEP), Gaussian Process Regression (GPR), and random forest (RF), are applied for predicting output parameters. So, drag, lift and side forces and also minimum and a maximum of pressure coefficients for mentioned wind directions and velocity are predicted and compared using statistical parameters. Obtained results indicated that RF in all coefficients of wind direction and most coefficients of free stream velocity provided the most accurate predictions. As a conclusion, RF may be recommended for the prediction of aerodynamic coefficients.

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