A Soft Sensor for Water-Content-in-Oil Based on GA-RBF Neural Network

Fluids from producing oil wells are mixtures of crude oil, water and sediments. Crude oil and water will form emulsion during drilling, producing, transporting and refinery processing of crude oil. It is very important to know the water-content-in-oil for oilfield production because the water content can be directly used to assess economic benefit for a single well, the wells in a zone and in an oil field. The proportion of the various constituents varies dramatically depending on the geologic formation from which the mixture fluid is produced and the stage at which the formation is in its production life cycle. Formations that have been newly tapped will normally produce fluids with very low fractional water content, typically 10% or less. This is called an oil continuous flow. For water contents between 25% and 75%, whether the flow is oil continuous or water continuous depends on the exact details of the flow conditions. Near the end of the formation production life cycle the water content will be very high. For example, in an old oilfield production, the water content range in oil from different wells in zone or wells from different zones is significantly different, some very high even more than 90% and the other less than 20%, and its temperature and salinity content changes with time. There is a demand on high performance and low price measuring instruments for a single well water-contentin-oil. Various measuring methods and their instruments for water-content-in-oil are researched and designed in many countries of the world[1~4]. However, so far, there are not any instruments with satisfactory in the performance/cost ratio and/or for the whole range of the water-content-in-oil from 0 to 100%. The conventional method is to periodically hook up each well to a test separator. Water content is often determined by sampling the test separator flow and centrifuging the sample. But this is unwieldy, not cost efficient, and labor intensive. One of the traditional water detection technologies was to measure capacitance, or the ability to store electricity[3]. A capacitance probe is generally installed inside a pipeline for determining fluid’s dielectric property. The problems are the dependence of dielectric properties on frequency and water formation salinity. The capacitance probe is generally applicable for the cases whereby oil is at a constant temperature with less than 10% water and no entrained gas. Another technique is called density inference device, which is generally utilized for the fluids containing 15-85% water contents[4]. When the oil and water densities are known, the device measures the density of the emulsion (the oil/water mixture), from which the oilto-water ratio can be inferred. However, density inference loses resolution in the heavy oil. Therefore, in such a situation, a better choice would be microwave sensors that work on the principle that oil and water absorb microwave energy differently and are not affected by the density difference between oil and water[5]. However, the accuracy of the sensors is affected by the changes in the water salinity and the oil density. Besides, there are technologies of radiation isotope and near infrared spectroscopy for predicting water content[6,7], but there are risks in safety and higher in cost of the instruments. There are a number of challenges which should be addressed in order to provide a practical solution to the measurement of the water-content-in-oil. A few are listed here.