Demulsifier Performance Ranking via Temperature-Grouped Histograms
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Solution Overview
Problem
Crude oil processing faces challenges in efficiently separating oil and water due to temperature fluctuations and production upsets, making it difficult to compare and rank demulsifier performance effectively.
Innovation Solution
A computer-implemented method that receives data from sensors at a Gas and Oil Separation Plant, determines demulsifier separation efficiencies based on flow rates and temperatures, groups efficiencies into temperature ranges, generates histograms, and ranks demulsifiers according to their performance, providing feedback for optimal demulsifier selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If demulsifiers are injected into crude oil emulsion to separate oil and water, then separation efficiency is improved, but temperature fluctuations and production upsets make it difficult to compare and rank demulsifier performance effectively
Solution Approach 1:
The patent transforms raw sensor data (flow rates, temperatures) into normalized performance metrics by grouping efficiencies into temperature ranges and generating histograms. This parameter transformation allows comparison of demulsifier performance across varying temperature conditions, resolving the contradiction between measurement precision and adaptability to varying conditions.
Solution Approach 2:
The patent introduces histograms as an intermediary representation between raw sensor data and demulsifier performance ranking. The histograms aggregate efficiency data across temperature ranges, serving as a mediator that enables reliable performance comparison despite temperature fluctuations and production upsets.
2Measurement precision
If multiple sensors measure flow rates and temperatures to determine separation efficiency, then measurement accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the continuous temperature data into discrete temperature ranges and groups efficiency measurements within each range. This segmentation simplifies the processing of multi-sensor data by organizing it into manageable bins, reducing computational complexity while maintaining measurement accuracy.
Solution Approach 2:
The patent creates histogram representations as simplified copies of the raw sensor data distribution. Instead of processing all raw flow rate and temperature measurements directly, the system creates aggregated histogram copies that capture the essential performance characteristics, reducing data processing complexity.
Data Source
AI summary
The present disclosure describes a method including: receiving input data from a gas and oil separation plant (GOSP), wherein: one or more demulsifiers is being injected into an emulsion to achieve a separation, a plurality of flow rates of water and the one or more demulsifiers are being measured inside the GOSP, the input data comprises the plurality of flow rates as well as temperatures corresponding to the plurality of flow rates, and determining, for each of the one or more demulsifiers, efficiencies of the separation based on the flow rates measured at corresponding temperatures; grouping respective efficiencies of separation according to a set of temperature ranges; and generating, for at least one temperature range, a histogram for the at least one temperature range; ranking the one or more demulsifiers according to the histogram; and providing a feedback to indicate a ranked order of the one or more demulsifiers.