[V10N2] – Journey of a Lab Sample From Collection to Analysis


Analysis of Products Quality is vital for the success of any manufacturing business to receive from raw material vendors or sell the final products to end users.

Various technologies are used in different businesses based on the types of their products. However, one aspect common in all businesses is to collect a sample to analyze quality.

In this article, we will discuss the journey of a lab sample from collection to analysis for a refinery.

Additionally, we will discuss how a refinery can estimate the cost and load of analyses in a lab environment only, not considering the online process analysis.

In the first part of this article, let us start our journey and walk with a lab sample for analysis in a lab.

1. Sample Collection

  • a.  Selection of Sample Point: Identify the appropriate sample point on tanks and process streams. This could be inline, at the bottom, middle, or top of a tank, or from a specific point in the process stream.
  • b.  Preparation of Equipment: Ensure all sampling equipment, such as bottles, valves, syringes, and containers, are clean and properly labeled.
  • c.  Collection Procedure: To avoid contamination, follow standard operating procedures (SOPs) for sampling. Use appropriate personal protective equipment (PPE).

2. Sample Transport

  • a.  Immediate Sealing: Seal the sample container immediately after collection to prevent contamination and evaporation.
  • b.  Labeling: Label the sample with relevant information, including the sample point, date, time, and other pertinent details.
  • c.  Transportation: Transport the sample to the laboratory under controlled conditions to prevent degradation. This may involve using coolers or insulated containers.

3. Sample Reception

  • a.  Registration: Upon arrival at the laboratory, the sample is logged into the laboratory information management system (LIMS) or a sample logbook. Details such as sample ID, collection point, and arrival time are recorded.
  • b.  Inspection: Inspect the sample for any signs of leakage, contamination, or improper labeling.

4. Sample Preparation

  • a.  Pre-treatment: Depending on the type of analysis required, the sample may need to be pre-treated. This can include filtering, diluting, or homogenizing.
  • b.  Sub-sampling: If multiple tests are to be conducted, the sample may be divided into aliquots.

5. Analysis

  • a.  Selection of Analytical Methods: Choose the appropriate analytical methods based on the sample type and the parameters to be measured (e.g., chromatography for hydrocarbon analysis and spectroscopy for element detection).
  • b.  Calibration: Calibrate analytical instruments to ensure accuracy. This involves using standards and blanks.
  • c.  Testing: Perform the analysis following standard methods (ASTM, ISO, etc.). Record all observations and data meticulously.

6. Data Processing

  • a.  Data Entry: Enter raw data into the LIMS or appropriate software for analysis.
  • b.  Quality Control: Apply quality control measures, such as running control samples and duplicates, to verify the accuracy and precision of the results.

7. Reporting

  • a.  Result Compilation: Compile the results into a report format, including relevant calculations and observations.
  • b.  Verification: Have a senior analyst or laboratory manager review and verify the results.

8. Communication of Results

  • a.  Distribution: Distribute the final report to stakeholders, including process engineers, quality control personnel, and operations managers.
  • b.  Feedback Loop: Discuss the results with the operations team to make necessary adjustments to the process or address any issues identified during analysis.

9. Record Keeping

  • a.  Documentation: Maintain records of the sample collection, analysis, and results for future reference and compliance with regulatory requirements.
  • b.  Archiving: Store samples and documentation securely for a specified period, depending on regulatory and company policies.

Now, let us discuss the management of sample collection from different refinery areas.

A refinery has two areas of operations, namely, onsite and offsite. Process units reside in the onsite area, and all storage, receipt, movement, and terminal operations are categorized as offsite operations.

As products are manufactured in both areas, their qualities are determined according to a schedule of sample collection and types of analyses performed.

How can we estimate the load on staff and lab and its cost?

OMS eLearning Academy has developed a methodology for this purpose.

We will discuss a case study to demonstrate the concept.


The case study started with a lab sample collection schedule and various qualities to be analyzed in a lab. A typical collection and analysis look like this for both tanks and process streams.

Fig. 1


Next, we defined a parameter based on the number of sample sources, how many samples are taken per collection schedule, and how many analyses are scheduled for that ample. This resulted in a parameter we called SSQ, as shown below.

Fig. 2

The yearly lab analysis lab can be calculated based on three samples collected daily to analyze two qualities for a process stream whole naphtha in onsite operations.

Yearly Load 2160 = 2 qualities 3 Daily Sample 365


Based on the collection frequencies, we calculated the yearly load for lab analyses for all samples and categorized them for onsite (process streams) and offsite (tanks) operations. The resulting plot has the following interesting observation.

  • Onsite Operations require large samples, more analyses and collected 3-4 times daily. This is expected to be a process stream quality change in real-time due to feed changes and updating operating parameters to optimize production.
  • Offsite Operations involving most tank samples are collected less frequently, like only 3 to 4 times weekly, require more samples due to the number of tanks, and require analyses of 18-20 qualities, say for blending.
Fig. 3


The above analysis of yearly lab cost was estimated conservatively for a 300 KN/Day refinery assuming workforce and lab analysis cost and is shown here.

This method can be updated for realistic workforce analysis based on collection and analysis costs.

For our study case, this ranged between 4 to 4,5 million Dollars per year.

Fig. 4


1.  Automation and Digitalization:

  • Automated Sampling Systems: Using automated sampling systems helps reduce manual labor, improve consistency, and minimize human error. These systems can be programmed to collect samples at regular intervals.
  • Digital Monitoring and Control: Implementing digital monitoring systems allows real-time tracking of sample collection and analysis processes. This can optimize the workflow and reduce unnecessary sample collections.

2.  Onsite and Mobile Labs:

  • Onsite Testing: Establishing onsite labs or portable lab units can reduce the time and cost of transporting samples to offsite facilities. Immediate analysis can lead to quicker decision-making and process adjustments.
  • Mobile Labs: Deploying mobile lab units to various parts of the refinery or field sites can ensure timely sample collection and analysis, reducing delays and associated costs.

3.  Improved Process Control:

  • Predictive Maintenance: Using predictive maintenance and monitoring techniques can help identify issues before they become critical, reducing the need for frequent sampling.
  • Optimized Sampling Strategies: Implementing optimized and risk-based sampling strategies ensures samples are collected only, when necessary, based on statistical methods and process criticality.

4.  Integrated Laboratory Information Management Systems (LIMS):

  • Data Management: Utilizing LIMS helps streamline data collection, analysis, and reporting processes, reducing manual data entry errors, and improving efficiency.
  • Workflow Automation: LIMS can automate workflows and integrate various lab instruments, reducing the time and cost involved in sample analysis.

5.  Enhanced Training and Procedures:

  • Staff Training: Regular training for staff on the latest sampling techniques and analysis methods can improve efficiency and reduce errors.
  • Standard Operating Procedures (SOPs): Implementing and strictly following SOPs ensures consistency and quality in sample collection and analysis, reducing rework and associated costs.

6.  Collaborations and Outsourcing:

  • Strategic Partnerships: Collaborating with specialized third-party labs for specific analyses can be cost-effective, especially for specialized or infrequent tests.
  • Outsourcing Routine Analyses: Outsourcing routine and high-volume analyses to external labs can free up in-house resources for more critical tasks, potentially reducing costs.


The journey of a lab sample from collection to analysis involves meticulous steps to ensure integrity and accuracy.

Proper sampling techniques, transportation, and systematic laboratory procedures are critical to obtaining reliable results that inform refinery operations and decision-making processes.


Academy Courses

  1. OEA5T-Analyzers and Sampling System
  2. OEA37T-Lab Analysis of Stock and Product Qualities
  3. OEA42TModel-Based Predictions of Tank Qualities
  4. OEA48T-Online Analysis of Stock and Header Qualities
  5. OEA83T-Tank Quality Analysis, Measurement, and Prediction

Online Webinar

Academy White Papers

  1. “Model-based Online Analysis and Monitoring of Tank Qualities”, Paper presented at AIChE Spring National Meeting, Houston, April 24, 2007
  2. “Advances In-Tank Quality Measurements Can Help Cut Operational Costs”, Hydrocarbon Processing, Vol-86, No-6, pp 67-70, June 2007

Disclaimer: OMS eLearning Academy and ChatGPT collaborated as Humans and AI to generate this article for you.

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