Deyuan Kong and Sara Mcmillen, Chevron Energy Technology Company USA

Slides:



Advertisements
Similar presentations
UNDERSTANDING ENVIRONMENTAL LABORATORY/QC REPORTS Maya Murshak – Merit Laboratories, Inc.
Advertisements

A U.S. Department of Energy Office of Science Laboratory Operated by The University of Chicago Office of Science U.S. Department of Energy Streamlined.
SESSION: MANAGING CONTAMINATION North Carolina DOT’s Experience with UV Fluorescence for Measuring Petroleum Contamination in Soil Cyrus Parker, LG P.E.,
Quantifying soil carbon and nitrogen under different types of vegetation cover using near infrared-spectroscopy: a case study from India J. Dinakaran*and.
Selectivity, Sensitivity, Signal to Noise, Detection Limit
RQflex ® - the pocket laboratory for quantitative on-site measurements in agriculture and horticulture
Establish Verification Procedures (Task 11 / Principle 6)
Summary 1 l The Analytical Problem l Data Handling.
.
Multipurpose analysis: soil, plant tissue, wood, fruits, oils. Benchtop, portable Validation in-built, ISO compliant Little or no sample preparation. Rapid.
QA/QC FOR ENVIRONMENTAL MEASUREMENT Unit 4: Module 13, Lecture 2.
Chemometrics Method comparison
Method Comparison A method comparison is done when: A lab is considering performing an assay they have not performed previously or Performing an assay.
CEMTREX, INC. MODCON SYSTEMS LTD NIR Systems July 2010.
2010 CEOS Field Reflectance Intercomparisons Lessons Learned K. Thome 1, N. Fox 2 1 NASA/GSFC, 2 National Physical Laboratory.
Site-Specific Management Factors influencing plant growth Water Light Temperature Soil Compaction Drainage.
10 / 07BRUINS INSTRUMENTS1 Training Near Infrared Transmission Whole Grain Analyzer.
1 Spectroscopic Analysis Part 1 – Introduction Chulalongkorn University, Bangkok, Thailand January 2012 Dr Ron Beckett Water Studies Centre School of Chemistry.
August 01, 2008 Performance Modeling John Meisenbacher, MasterCard Worldwide.
Chem. 31 – 9/23 Lecture Guest Lecture Dr. Roy Dixon.
Measurement Uncertainties Physics 161 University Physics Lab I Fall 2007.
1 / 9 ASTM D19 Method Validation Procedures William Lipps Analytical & Measuring Instrument Division July, 2015.
Chapter 5 Errors In Chemical Analyses Mean, arithmetic mean, and average (x) are synonyms for the quantity obtained by dividing the sum of replicate measurements.
Crop Spec, A Collaborative Partnership A real time integrated plant nutrient monitoring and application system for Agricultural equipment.
Food Quality Evaluation Techniques Beyond the Visible Spectrum Murat Balaban Professor, and Chair of Food Process Engineering Chemical and Materials Engineering.
PID Gas Meter/Detector. Introduction Air monitoring data is useful for: *Assessing the health risks to the public and response workers. *Selecting personal.
Potential Errors In Epidemiologic Studies Bias Dr. Sherine Shawky III.
ME551/GEO551 Introduction to Geology of Industrial Minerals Spring 2005 SAMPLING.
5. Quality Assurance and Calibration Quality assurance is We do to get the right answer for our purpose. Have Sufficient accuracy and precision to support.
1 of 27 The EPA 7-Step DQO Process Step 5 - Define Decision Rules (15 minutes) Presenter: Sebastian Tindall Day 2 DQO Training Course Module 5.
FTIR Fourier Transform Infrared. FTIR Introduction Air monitoring data is useful for: *Assessing the health risks to the public and response workers.
Validation Defination Establishing documentary evidence which provides a high degree of assurance that specification process will consistently produce.
Rapid, On-site Identification of Oil Contaminated Soils Using Visible Near-Infrared Diffuse Reflectance Spectroscopy Chakraborty, S. 1, D. Weindorf 1,
Emission source sampling and monitoring Topic 6 Ms Sherina Kamal May
Measuring Soil Properties in situ using Diffuse Reflectance Spectroscopy Travis H. Waiser, Cristine L. Morgan Texas A&M University, College Station, Texas.
LECTURE 13 QUALITY ASSURANCE METHOD VALIDATION
Global predictors of regression fidelity A single number to characterize the overall quality of the surrogate. Equivalence measures –Coefficient of multiple.
COMPARISON OF NATURAL SOURCE DEPLETION (NSZD) CHARACTERIZATION METHODS Mark Malander and Harley Hopkins (ExxonMobil) Andy Pennington, Jonathon Smith, and.
1 FORMER COS COB POWER PLANT From Characterization to Redevelopment Brownfields2006 November 14, 2006.
How to ensure Safety? Calibration vs Functional (Bump)Test Differentiate between calibration and functional (bump) test functional test –the sensors.
Introduction to Quality Assurance. Quality assurance vs. Quality control.
Quality Assurance.
Quality Assessment.
Precise Print Color Control
2.1 & 2.2: Rainfall Detection and Alarm System
An oil company in Canada
Ethylene Furnace High Temperature Cameras
Development of PAT tools using guided microwave spectroscopy and chemometrics for meat and dairy processing applications Ming Zhao,¹ Bhavya Panikuttira,¹.
Quality Assurance in the clinical laboratory
IncuCyte Training Calibrations and Troubleshooting
Ali. M. Al-Turki Hesham M. Ibrahim
RAPID DETERMINATION OF PROTEIN CONTENT IN PROTEIN POWDER FINISHED PRODUCT USING NEARINFRARED (NIR) Roney Christiana, Yanjun Zhangb, Kan Heb, Piyush Purohita,
Soils 5.02: Discuss the soil profile and soil sampling for surface and subsurface layers.
12 Inferential Analysis.
Strategies for Eliminating Interferences in Optical Emission Spectroscopy Best practices to optimize your method and correct for interferences to produce.
Ethylene Furnace High Temperature Cameras
Deyuan Kong, Brian Morlan, Roopa Kamath, and Sara Mcmillen
Analytical Method Validation
Assessing oyster reef habitat value through naked goby
Chapter 5 Quality Assurance and Calibration Methods
Choice of Methods and Instruments
ME551/GEO551 Introduction to Geology of Industrial Minerals Spring 2007 SAMPLING.
Effective Measurement and Monitoring of Total Petroleum Hydrocarbons with Field Equipment Patrick Tyczynski M-I SWACO, a Schlumberger company.
12 Inferential Analysis.
JMP 11 added new features and improvements to CCB and MSA.
Introduction To Medical Technology
Korea Hydro & Nuclear Power Company Seulki Kim
Introduction to Analytical Chemistry
Quality Assessment The goal of laboratory analysis is to provide the accurate, reliable and timeliness result Quality assurance The overall program that.
Presentation transcript:

Deyuan Kong and Sara Mcmillen, Chevron Energy Technology Company USA An IR-Based Rapid Field Analytical Method for TPH Measurement - Field Deployment and Performance Evaluation Deyuan Kong and Sara Mcmillen, Chevron Energy Technology Company USA Timothy Vidra, Yohanes Kurniawan, Sarah Chitra, Dicky Saputra and Dion Kumboro PT. Chevron Pacific Indonesia

Project Background Opportunity Soil samples from hydrocarbon impacted soil in exploration and production operations need to be tested for Total Petroleum Hydrocarbon (TPH) Delays in sample analyses and decision making due to large # of soil samples per week needing analysis Lab analysis can take 2-4 weeks Approach Development of rapid TPH analytical method to increase accuracy and efficiency 1) Real-time remediation process monitoring 2) Reducing the number of samples going to lab

Handheld IR Instrument for Non-Destructive TPH Measurement Portable handheld IR instrument Diffuse reflectance of IR light reflected from the sample The world’s first handheld instrument for the direct measurement of TPH in soil User simply pulls the trigger for a 15 second reading of TPH (C10-C36) in mg/kg IR light is emitted Interacts with the surface of the sample Light is diffusely reflected back to detector IR spectrum (readout) is produced

Field Pilot Approach Load the Calibration Model on to Instrument Collect field Soil Samples Load the Calibration Model on to Instrument Potential Field Deployment Process samples (split) IR analysis Collecting soil samples at the field sites; Get representative sample drying and homogenizing the samples and screened to less than 2mm in size; Each sample get well mixed “averaged” analyzed 5 times by FTIR-ATR; Obtain a good average IR spectrum and developing a site-specific chemometric model; Testing the calibrated model against a separate set of validation samples to determine how reliably the calibrated instrument measured soil TPH concentration; Determining the minimum detection threshold for the each sites. Build Model Using Partial Least Square Method Predict TPH values and validation tests completed with blind samples Reference Lab GC-FID

Pilot Studies Results Evaluation – Field A Calibration model completed with 111 soil samples from Field A at TPH range 0-120,000 mg/kg Using calibration model A vs. GCFID Data for validation Test Validation Samples (•)& Calibration Samples () Outliner analysis - spectrum suggests the high clay contents of those samples Detection limit of this model - 170 mg/kg

Pilots Studies Results Evaluation – Field B Calibration model completed with 200 soil samples from Field B at TPH range 0-50,000 mg/kg Using calibration model B vs. GCFID Data for validation Test Validation Samples (•)& Calibration Samples () Detection limit of this model- 380 mg/kg

Correlation Coefficients Relative Standard Deviation* Accuracy for Various Assay Ranges for Calibration Samples for Soils in Two Different Oil Fields (A & B) Field A (wide range of calibration up to 12%) Field B (limited calibration up to 5%) Assay Ranges (mg/kg TPH) RMSECV mg/kg TPH Correlation Coefficients (r2) 0 - 3,000 170 0.92 3,000 - 5,000 184 0.96 5,000 - 15,000 410 0.98 15,000 - 30,000 803 0.99 30,000 - 120,000 2,375 Assay Range   (mg/kg TPH) RMSECV Relative Standard Deviation* (%) 0 - 5,000 376 n/a 5,000 – 15,000 930 ≤ 19 15,000 – 20,000 1,390 ≤ 9 20,000 – 30,000 2,107 ≤ 11 30,000 – 50,000 2,815 RMSECV: Root-mean-square Error of Cross-Validation

Field Application- For Existing Soil Stockpiles RemScan works best when the soil is dry & sample is measured directly on site

Field Application- What Can We do to Meet the 5% Free Moisture Requirement? if the soil is wet, measurement can be done after drying the sample Or Press the soil sample into the drying tray and use the drying box to dry the sample in 30 minutes/36 samples Samples put in drying in the morning can be measured for TPH in the afternoon

Collection of samples from multiple sites Field Application How RemScan is used in different operational settings Other scenario: when the sample is wet, measurement can be done after drying the sample. Measurement at office Collection of samples from multiple sites For samples that need longer drying time, RemScan is not readily available on site, and the result is reported the next day

Field Deployment – Model Performance Check 3-5 RemScan units deployed for field TPH measurements Monthly split sampling program established to monitor the accuracy 70% of the handheld IR measured data are within +/- 30% of Lab GCFID results

Data Check - Precision Evaluation Homogenize samples and divide into 5 sub-samples Measure each sub-sample 3 times Test with RemScan using the same sample to check precision and repeatability Sample ID Soil Type Color REMSCAN RSD (%) % mg/Kg DR-01 Clayey Silt Dark Brown 2.36 23,600 6.02 DR-02 2.54 25,400 9.05 DR-03 1.99 19,920 10.86 DR-04 1.92 19,220 2.45 DR-05 2.29 22,860 5.20 DR-06 Light Brown 0.25 2,473 9.60 DR-07 Brown 1.23 12,340 5.52 DR-08 2.67 26,747 11.80

Summary This portable handheld IR Instrument will enable rapid and accurate delineation of sites & allows real time process monitoring for different remediation technologies Significant time reductions Real-time process monitoring Rapid, field-based testing Improve data density for site assessment Less waiting time for soil excavation and transport Improved Safety Prevents worker exposure and generation of waste by eliminating the use of solvents (used in the lab and in other field test methods) Potential Cost Savings

Slide 14 Acknowledgements The authors gratefully acknowledge the support and discussion from Ziltek Pty. Ltd and ALS lab in Bogor, Indonesia for deployment of Handheld IR Instrument