scholarly journals Forecast of the deposition of sulfate salts, taking into account the content of strontium, in the exploitation of oil deposits

2017 ◽  
pp. 55-63
Author(s):  
T. A. Kireeva ◽  
R. I. Minikaeva ◽  
L. A. Anisimov
Keyword(s):  
Computer Modeling ◽  
Reservoir Pressure ◽  
The Caspian Sea ◽  
Strontium Content ◽  
Reservoir Conditions ◽  
Sulphate Deposition ◽  
Oil Deposits ◽  
Sulfate Salts ◽  
Sulphate Salts

Based on the experience of developing an oil fieled on the Caspian Sea shelf, which was initially operated with injection of seawater into oil-bearing seams to maintain reservoir pressure, a forecast was made for the deposition of sulfate salts in reservoir conditions. The forecast of sulphate deposition is carried out in two ways: analytical calculations by the method of J.E. Oddo and M.B. Thomson and computer modeling. The prognosis took into account the strontium content in the reservoir waters of the deposit, which is usually ignored in oilfield practice. It has been established that computer modeling gives a more accurate prediction, in particular, considerably expands the temperature limits of anhydrite precipitation. The determination of the amount of potentially sulphate salts potentially found in computer simulations has shown that the mass of deposited calcium and strontium sulfates is large enough that it can significantly reduce the permeability of the reservoir.

Machine Learning Predictive Models to Estimate the Minimum Miscibility Pressure of CO2-Oil System

2021 ◽  
Author(s):  
Abderraouf Chemmakh ◽  
Ahmed Merzoug ◽  
Habib Ouadi ◽  
Abdelhak Ladmia ◽  
Vamegh Rasouli
Keyword(s):  
Machine Learning ◽  
Predictive Models ◽  
Critical Parameters ◽  
Co2 Injection ◽  
Learning Models ◽  
Minimum Miscibility Pressure ◽  
Reservoir Conditions ◽  
Important Amount ◽  
Machine Learning Models

Abstract One of the most critical parameters of the CO2 injection (for EOR purposes) is the Minimum Miscibility Pressure MMP. The determination of this parameter is crucial for the success of the operation. Different experimental, analytical, and statistical technics are used to predict the MMP. Nevertheless, experimental technics are costly and tedious, while correlations are used for specific reservoir conditions. Based on that, the purpose of this paper is to build machine learning models aiming to predict the MMP efficiently and in broad-based reservoir conditions. Two ML models are proposed for both pure CO2 and non-pure CO2 injection. An important amount of data collected from literature is used in this work. The ANN and SVR-GA models have shown enhanced performance comparing to existing correlations in literature for both the pure and non-pure models, with a coefficient of R2 0.98, 0.93 and 0.96, 0.93 respectively, which confirms that the proposed models are reliable and ready to use.

scholarly journals Production Optimization for Natural Flow and ESP Well A Case Study on Well NS-5 Mishrif Formation-Nasriya Oil Field

2020 ◽  
Vol 10 (2) ◽  
pp. 17-35
Author(s):  
Hamzah Amer Abdulameer ◽  
Dr. Sameera Hamd-Allah
Keyword(s):  
Production Rate ◽  
Production Optimization ◽  
Oil Field ◽  
Reservoir Pressure ◽  
Pump Frequency ◽  
Individual Parameter ◽  
Well Production ◽  
Well Design ◽  
Natural Flow ◽  
Reservoir Conditions

As the reservoir conditions are in continuous changing during its life, well production rateand its performance will change and it needs to re-model according to the current situationsand to keep the production rate as high as possible.Well productivity is affected by changing in reservoir pressure, water cut, tubing size andwellhead pressure. For electrical submersible pump (ESP), it will also affected by numberof stages and operating frequency.In general, the production rate increases when reservoir pressure increases and/or water cutdecreases. Also the flow rate increase when tubing size increases and/or wellhead pressuredecreases. For ESP well, production rate increases when number of stages is increasedand/or pump frequency is increased.In this study, a nodal analysis software was used to design one well with natural flow andother with ESP. Reservoir, fluid and well information are taken from actual data of Mishrifformation-Nasriya oil field/ NS-5 well. Well design steps and data required in the modelwill be displayed and the optimization sensitivity keys will be applied on the model todetermine the effect of each individual parameter or when it combined with another one.

scholarly journals Determination of gas-saturated oil density at reservoir conditions and development of quality control index of PVT laboratory report

2020 ◽  
Author(s):  
Muhammad Ali Al-Marhoun
Keyword(s):  
Quality Control ◽  
Production Engineering ◽  
Accuracy Estimate ◽  
Bubble Point ◽  
Laboratory Report ◽  
Reservoir Conditions ◽  
Data Yield ◽  
Oil Density

AbstractThe oil density at the bubble point is an important thermodynamic property required in reservoir simulation and production engineering. A higher-accuracy estimate of this property would improve the accuracy of reservoir and production engineering calculations. The bubble point oil density is obtained either from separator tests of reservoir fluids or from differential gas liberation tests. A new procedure utilizing separator and differential tests is proposed whereby the experimental data yield a unique value with high accuracy for the bubble point oil density. A consistent correction of other PVT properties, which are influenced by the bubble point oil density, is required to reflect the unique density value. A quantitative quality control index is defined to measure the quality of PVT laboratory reports. This is achieved by utilizing the unique property of the bubble point oil density, which is usually ignored.

Direct-Current Arc Determination of Strontium in Calcites

1967 ◽  
Vol 21 (3) ◽  
pp. 157-159 ◽  
Author(s):  
A. L. Schalge ◽  
B. D. McCarty
Keyword(s):  
Direct Current ◽  
Short Exposure ◽  
Strontium Content ◽  
Arc Excitation

The method described herein employs low-current de-arc excitation, short exposure times, and a selected portion of the analytical gap to analyze small amounts (0.33–1.0 mg) of carbonate samples mixed with graphite for their strontium content. Repeatability of the method is 6%.

scholarly journals Selection of Method of Chemical Analysis in Measuring the Salinity of Mineral Materials

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 559
Author(s):  
Teresa Stryszewska ◽  
Marta Dudek
Keyword(s):  
High Performance ◽  
Salt Content ◽  
Technical Condition ◽  
Water Soluble ◽  
Aqueous Extracts ◽  
X Ray ◽  
Chloride Salts ◽  
Sulphate Salts ◽  
Selection Of

The article deals with the issue of salt content in brick buildings, which plays an important role in the assessment of the technical condition, in particular of historic buildings. A question has been asked about the selection of the best research method to determine the salinity of mineral materials. To obtain the answer, the authors conducted some tests on ceramic bricks salted with seven types of salt solutions. Research methods such as: spectrophotometry (UV), ion chromatography (High Performance Liquid Chromatography (HPLC)), X-Ray Fluorescence Spectrometry (XRF) and Energy-Dispersive X-Ray Spectroscopy (EDS) were compared. The above methods belong to two groups: the first is based on aqueous extracts and allows the determination of water-soluble salts, and the second concerns testing directly on the sample so that insoluble salts can also be determined. The results tests indicate that the methods based on solid phases (XRF and EDS) give higher salinity values than those based on aqueous extracts (HPLC and UV). The results were also analysed with regard to the type of salt. Larger differences are observed for sulphate salts while chloride salts are characterised by smaller differences. On this basis, it is concluded that the salt content of the material is best assessed using tests that make it possible to recognise the salt in question and its quantity.

Determination of the Structure of Distorted TiO6Units in the Titanosilicate ETS-10 by a Combination of X-ray Absorption Spectroscopy and Computer Modeling

1996 ◽  
Vol 100 (2) ◽  
pp. 449-452 ◽  
Author(s):  
Gopinathan Sankar ◽  
Robert G. Bell ◽  
John Meurig Thomas ◽  
Michael W. Anderson ◽  
Paul A. Wright ◽  
...  
Keyword(s):  
Computer Modeling ◽  
Absorption Spectroscopy ◽  
X Ray ◽  
X Ray Absorption
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