Method and device for electrostatic desalter optimization for enhanced metal and amine removal from crude oil

Abstract

A method for removing calcium, iron, other metals, and amines from crude oil in a refinery desalting process includes the steps of: running a plurality of tests to determine at least one statistically significant processing characteristic of the refinery desalting process; adding a wash water to the crude oil; adding the wash water to the crude oil to create an emulsion; adding to the wash water, the crude oil or the emulsion an acid additive consisting of at least one of the following: oxalic acid, citric acid, water-soluble hydroxyacid selected from the group consisting of glycolic acid, gluconic acid, C.sub.2-C.sub.4 alpha-hydroxy acids, malic acid, lactic acid, poly-hydroxy carboxylic acids, thioglycolic acid, chloroacetic acid, polymeric forms of the above hydroxyacids, poly-glycolic esters, glycolate ethers, and ammonium salt and alkali metal salts of these hydroxyacids, and mixtures thereof; resolving the emulsion containing the acid additive into a hydrocarbon phase and an aqueous phase; and adjusting a control setting of the processing characteristic as a function of the tests.

Description

FIELD OF THE INVENTION

The present invention relates to a method and device for determining the statistically optimal desalter parameter settings for removing metals, amines and other contaminants from crude oil at minimum cost via electrostatic coalescence.

BACKGROUND INFORMATION

U.S. Pat. No. 4,853,109 discloses a method for removing metal contaminants, particularly iron and non-porphyrin, organically-bound iron components from crude petroleum. This process comprises mixing crude oil with an aqueous solution of hydroxo-carboxylic acids or salts thereof, preferably citric acid, and separating the aqueous solution and metals from the crude.

U.S. Pat. No. 5,078,858 discloses a method for extracting iron species from crude oil by directly adding oxalic or citric acid to the crude oil feedstock, mixing the acid and oil, then adding wash water to form a water in oil emulsion. The emulsion is resolved separating the aqueous solution and metals from the crude.

U.S. Pat. No. 7,497,943 discloses a method for transferring metals and/or amines from a hydrocarbon phase to a water phase in an oil refinery desalting process. The method consists of adding to a wash water an effective amount of a composition comprising certain water-soluble hydroxyacids to transfer metals and/or amines from a hydrocarbon phase to a water phase. The water-soluble hydroxyacid is selected from the group consisting of glycolic acid, gluconic acid, C.sub.2-C.sub.4 alpha-hydroxyacids, malic acid, lactic acid, poly-hydroxy carboxylic acids, thioglycolic acid, chloroacetic acid, polymeric forms of the above hydroxyacids, poly-glycolic esters, glycolate ethers, ammonium salt and alkali metal salts of these hydroxyacids, and mixtures thereof. The pH of the wash water is lowered to 6 or below, before, during and/or after adding the composition and the wash water is added to crude oil to create an emulsion. Finally, the emulsion is resolved into the hydrocarbon phase and an aqueous phase using electrostatic coalescence, where at least a portion of the metals and/or amines are transferred to the aqueous phase.

Optimum Temperature in the Electrostatic Desalting of Maya Crude Oil by Pruneda et al published in the 2005 Journal of the Mexican Chemical Society discloses a simulation model which suggests that there is an optimum temperature to maximize economic benefit when desalting heavy crude oil. As indicated in the art, an increase in process temperature has two effects to be considered. First, as temperature is increased, there is a corresponding decrease in oil density and viscosity which implies a significant increase in the settling rate of water droplets within the oil phase thus allowing a greater amount of oil to be processed resulting in an increase in profit from performing oil desalting. However, crude oil conductivity increases exponentially with temperature which implies a higher rate of electrical power consumption during electrostatic coalescence which increases processing expense.

Basic Statistics by Kiemele et al published in 1991 discloses basic statistical hypothesis testing techniques and statistical design techniques. In the techniques outlined by Kiemele et al, all decision-making operations are made by a human operator.

U.S. Pat. No. 4,853,109, U.S. Pat. No. 5,078,858, U.S. Pat. No. 7,497,943, Optimum Temperature in the Electrostatic Desalting of Maya Crude Oil by Pruneda et al, and Basic Statistics by Kiemele et al are hereby incorporated by reference herein.

SUMMARY OF THE INVENTION

The present invention provides a method for removing calcium, iron, other metals, and amines from crude oil in a refinery desalting process includes the steps of: running a plurality of tests to determine at least one statistically significant processing characteristic of the refinery desalting process; adding a wash water to the crude oil; adding the wash water to the crude oil to create an emulsion; adding to the wash water, the crude oil or the emulsion an acid additive consisting of at least one of the following: oxalic acid, citric acid, water-soluble hydroxyacid selected from the group consisting of glycolic acid, gluconic acid, C.sub.2-C.sub.4 alpha-hydroxy acids, malic acid, lactic acid, poly-hydroxy carboxylic acids, thioglycolic acid, chloroacetic acid, polymeric forms of the above hydroxyacids, poly-glycolic esters, glycolate ethers, and ammonium salt and alkali metal salts of these hydroxyacids, and mixtures thereof; resolving the emulsion containing the acid additive into a hydrocarbon phase and an aqueous phase; and adjusting a control setting of the processing characteristic as a function of the tests.

The present invention also provides a method for improving a refinery desalting process comprising the steps of: providing a range of values for at least one candidate variable representing a desalting process characteristic; performing a statistical calculation to determine at least one statistically significant candidate variable of the at least one candidate variable which is statistically significant for improving the refinery desalting process; and adjusting a control setting of the desalting process as a function of the statistical calculation.

An oil refinery, desalter and laboratory equipment are also provided.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a block diagram of a typical single stage crude oil electrostatic desalting mechanism according to one embodiment of the present invention;

FIG. 2 shows a block diagram of a typical first stage dehydration followed by a second stage electrostatic desalting mechanism according to one embodiment of the present invention;

FIG. 3 shows a block diagram of a typical two stage electrostatic desalting mechanism according to one embodiment of the present invention;

FIG. 4 shows an algorithm diagram for a multiple variable, two-level statistical quantification and estimation of performance for a given crude oil desalter according to one embodiment of the present invention;

FIG. 5 shows a diagram of one embodiment of the method of the present invention for a typical crude oil desalting operation.

DETAILED DESCRIPTION

FIG. 1 shows a diagram of a single stage crude oil electrostatic desalting mechanism 1000 of the present invention.

The desalting mechanism 1000 of the present invention includes a crude oil supply 10 for storing crude oil. The crude oil supply 10 is connected to a controllable pump 70 which is connected to an optional controllable fluid mixer 80. The optional controllable fluid mixer 80 allows an emulsion of crude oil 10, wash water 20, and acid additive 30 to be created prior to heating based upon the specific characteristics of the crude oil supply 10 to be desalted. The optional controllable fluid mixer 80, if necessary to process the crude oil supply 10, is controlled by the controller 110 to create and maintain the proper emulsion mix of crude oil 10, wash water 20, and acid additive 30.

Following either the controllable pump 70 or the optional controllable fluid mixer 80 is a controllable flow control valve (FCV) 120. The controllable flow control valve 120 and the controllable pump 70 work in conjunction under command of the controller 110 to control and maintain the crude oil feed rate and pressure. The crude oil 10 or crude oil emulsion created via optional controllable fluid mixer 80 is then heated to a desired processing temperature by the heater 130 which is controlled by controller 110.

The desalting mechanism 1000 of the present invention also includes a wash water supply 20 and an acid additive supply 30. In the embodiment of FIG. 1, as is preferred, the acid additive 30 is mixed with the wash water 20 by the controllable fluid mixer 40 before the crude oil/wash water emulsion is formed. Alternatively, the acid additive 30 could be mixed with the wash water 20 and crude oil 10 during the emulsion creation or after water-oil emulsion creation or with the crude oil 10. The fluid mixer 40 is controlled by the controller 110 to create and maintain the proper solution mixture of acid additive 30 and wash water 20. The acid additive 30 can be selected from the group consisting of oxalic acid, citric acid, glycolic acid, gluconic acid, C.sub.2-C.sub.4 alpha-hydroxy acids, malic acid, lactic acid, poly-hydroxy carboxylic acids, thioglycolic acid, chloroacetic acid, polymeric forms of the above hydroxyacids, poly-glycolic esters, glycolate ethers, and ammonium salt and alkali metal salts of these hydroxyacids, and mixtures thereof.

After mixing the solution of acid additive 30 and wash water 20 with the controllable fluid mixer 40, the resulting solution is input to a controllable flow control valve 90 which is used to allow samples of the mixed acid additive 30 and wash water 20 solution to be measured at a measurement station 200. Measurements made on the solution samples would include but not be limited to solution pH, solution impurity levels, and percentage of acid additive 30 to wash water 20. This information is sent to the controller 110.

After mixing the solution of acid additive 30 and wash water 20 with the controllable fluid mixer 40, the resulting solution is also input to a controllable pump 50 whose output is connected to a controllable flow control valve 60. The controllable pump 50 and the flow control valve 60 work in conjunction under the command of the controller 110 to control and maintain the wash water/acid solution feed rate and pressure. In the embodiment of FIG. 1, the controllable flow control valve 60 is shown to be a three-way valve to allow for emulsion creation with the crude oil supply 10 via the optional controllable fluid mixer 80, the optional controllable fluid mixer 140, or both. Like the optional controllable fluid mixer 80, the optional controllable fluid mixer 140, if necessary to process the crude oil supply 10, is controlled by the controller 110 to create and maintain the proper emulsion mix of crude oil 10, wash water 20, and acid additive 30. The controllable flow control valve 60 also allows for the acid additive 30 and wash water 20 solution to be presented to the optional controllable fluid mixer 80 and optional controllable fluid mixer 140 at the same or different flow rates when both mixer devices are used in the desalting process.

Following the optional controllable fluid mixer 140, the emulsion passes through a pressure control valve 160 before entering the electrostatic desalter 170. The electrostatic desalter 170 includes a liquid level sensor (LS) 210 used to measure the aqueous level in the electrostatic desalter 170. In the embodiment of FIG. 1, the measurement output of the liquid level sensor 210 is routed to the controller 110. The controller 110 uses the liquid level measurement data to control the controllable flow control valve 220 to drain the effluent from the electrostatic desalter 170 and control the aqueous layer and emulsion layer within the electrostatic desalter 170. Alternatively, the liquid level sensor 210 output may be directly connected to a level control valve instead of the controllable flow control valve 220 to drain the effluent. The controllable flow control valve 220 is also configured to allow samples of the effluent solution to be measured at a measurement station 200. Measurements made on the solution samples would include but not be limited to solution pH, solution impurity levels, temperature, and amount of residual oil present in the effluent. This information is sent to the controller 110.

The electrical power supply 150 provides the voltage necessary to create the electric field necessary for electrostatic coalescence in the electrostatic desalter 170. The controller 110 controls the electrical power supply 150 output. The electrical power supply 150 output may be static (i.e. constant voltage with a current limit) or, preferably, able to change key parameters to enhance the desalting operation. The electrical power supply 150 under the control of the controller 110 would preferably be able to alter its' output to include but not be limited to changes in the voltage level applied to the electrostatic desalter 170, the voltage waveform applied to the electrostatic desalter 170, current limits (if any) on the electrical power supply 150, or any combination thereof.

The desalted crude output of the electrostatic desalter 170 passes through a pressure control valve 180 and a controllable flow control valve 190. The controllable flow control valve 190 has two outputs to direct the desalted crude oil. Under control of the controller 110, the controllable flow control valve 190 controls and maintains the flow rate of desalted crude oil to the remaining refinery operations. Additionally, under control of the controller 110, the controllable flow control valve 190 can also direct samples of the desalted crude to the measurement station 200. Measurements made on the solution samples would include but not be limited to impurity levels, temperature, residual acid additive 30 and wash water 20 solution, etc. This information is sent to the controller 110.

The controller 110 can adjust various parameters of the desalting operation including but not limited to the following:

The crude oil supply 10 feed rate through the controllable pump 70 and controllable flow control valve 120

The temperature of the crude oil supply 10 or, optionally, the emulsion created by mixing the crude oil supply 10 with a solution comprising the acid additive 30 and/or wash water 20 through the controllable heater 130.

The solution mixture of acid additive 30 and wash water 20 through the controllable fluid mixer 40.

The flow rate of the solution mixture of acid additive 30 and wash water 20 through the controllable pump 50 and controllable flow control valve 60.

The emulsion formation through optional controllable fluid mixer 80 and/or optional controllable fluid mixer 140.

The electrostatic desalter 170 electric field through the controllable electrical power supply 150.

Control of the electrostatic desalter water level and emulsion layers through the liquid level sensor 210, the controllable flow control valve 220, and the controllable flow control valve 190.

As different tests are conducted with the desalting mechanism 1000, the parameters are adjusted per the test matrix and the selected product measurements are made after desalting the crude oil supply 10. The memory/data storage 100 function of the desalting mechanism 1000 allows the controller to access and update, if required, the control settings required to conduct the test matrix tests and store the measured data.

FIG. 2 shows a diagram of a typical first stage dehydration followed by a second stage electrostatic desalting mechanism 2000 of the present invention.

The desalting mechanism 2000 of the present invention includes a crude oil supply 2010 for storing crude oil. The crude oil supply 2010 is connected to a controllable pump 2070 whose output is connected to a controllable flow control valve (FCV) 2120. The controllable flow control valve 2120 and the controllable pump 2070 work in conjunction under command of the controller 2110 to control and maintain the crude oil feed rate and pressure. The crude oil 2010 is then heated to a desired processing temperature by the heater 2130 which is controlled by controller 2110. In the embodiment of FIG. 2, the heated crude oil passes through a pressure control valve 2160 before entering the dehydration mechanism 2310. The dehydration mechanism 2310 is designed to remove high salinity water from the crude oil supply 2010. The dehydration process relies on establishing a varying high voltage electric field in the oil phase of the dehydration mechanism 2310. Due to the action of the imposed electric field, the droplets are agitated causing the drops to coalesce into droplets of sufficient size to migrate via gravity to the lower water phase of the dehydration mechanism 2310. The dehydration mechanism 2310 includes a liquid level sensor (LS) 2340 used to measure the water level in the dehydration mechanism 2310. In the embodiment of FIG. 2, the measurement output of the liquid level sensor 2340 is routed to the controller 2110. The controller 2110 uses the liquid level measurement data to control the controllable flow control valve 2330 to drain the waste water from the dehydration mechanism 2310 and control the water layer and oil layer within the dehydration mechanism 2310. Alternatively, the liquid level sensor 2340 output may be directly connected to a level control valve instead of the controllable flow control valve 2330 to drain the waste water. The controllable flow control valve 2330 is also configured to allow samples of the effluent solution to be measured at a measurement station 2200. Measurements made on the solution samples would include but not be limited to solution pH, solution impurity levels, temperature, and amount of residual oil present in the waste water. This information is sent to the controller 2110.

The electrical power supply 2300 provides the voltage necessary to create the electric field necessary for water coalescence in the dehydration mechanism 2310. The controller 2110 controls the electrical power supply 2300 output. The electrical power supply 2300 output may be static (i.e. constant voltage with a current limit) or, preferably, able to change key parameters to enhance the dehydration operation. The electrical power supply 2300 under the control of the controller 2110 would preferably be able to alter its' output to include but not be limited to changes in the voltage level applied to the dehydration mechanism 2310, the voltage waveform applied to the dehydrator, current limits (if any) on the electrical power supply 2300, or any combination thereof.

The crude output of the dehydration mechanism 2310 passes through a pressure control valve 2320 on its way to the controllable fluid mixer 2350. The controllable fluid mixer 2350 allows an emulsion of crude oil 2010, wash water 2020, and acid additive 2030 to be created based upon the specific characteristics of the crude oil supply 2010 to be desalted. The controllable fluid mixer 2350 is controlled by the controller 2110 to create and maintain the proper emulsion mix of crude oil 2010, wash water 2020, and acid additive 2030.

The desalting mechanism 2000 of the present invention also includes a wash water supply 2020 and a acid additive supply 2030. In the embodiment of FIG. 2, as is preferred, the acid additive 2030 is mixed with the wash water 2020 by the controllable fluid mixer 2040 before the crude oil/wash water emulsion is formed. Alternatively, the acid additive 2030 could be mixed with the wash water 2020 and crude oil 2010 during the emulsion creation or after emulsion creation or with the crude oil 2010 itself. The fluid mixer 2040 is controlled by the controller 2110 to create and maintain the proper solution mixture of acid additive 2030 and wash water 2020. The acid additive 2030 can be selected from the group consisting of oxalic acid, citric acid, glycolic acid, gluconic acid, C.sub.2-C.sub.4 alpha-hydroxy acids, malic acid, lactic acid, poly-hydroxy carboxylic acids, thioglycolic acid, chloroacetic acid, polymeric forms of the above hydroxyacids, poly-glycolic esters, glycolate ethers, and ammonium salt and alkali metal salts of these hydroxyacids, and mixtures thereof.

After mixing the solution of acid additive 2030 and wash water 2020 with the controllable fluid mixer 2040, the resulting solution is input to a controllable flow control valve 2090 which is used to allow samples of the mixed acid additive 2030 and wash water 2020 solution to be measured at a measurement station 2200. Measurements made on the solution samples would include but not be limited to solution pH, solution impurity levels, and percentage of acid additive 2030 to wash water 2020. This information is sent to the controller 2110.

After mixing the solution of acid additive 2030 and wash water 2020 with the controllable fluid mixer 2040, the resulting solution is also input to a controllable pump 2050 whose output is connected to a controllable flow control valve 2060. The controllable pump 2050 and the flow control valve 2060 work in conjunction under the command of the controller 2110 to control and maintain the wash water/acid solution feed rate and pressure. The output of the flow control valve 2060 is an input to the controllable fluid mixer 2350 where the emulsion of crude oil 2010, wash water 2020, and acid additive 2030 is formed.

After mixing the crude oil 2010, acid additive 2030, and wash water 2020 in the controllable fluid mixer 2350, the resulting emulsion passes through a controllable flow control valve 2360 before entering the electrostatic desalter 2170. The controllable flow control valve 2360, under command of the controller 2110, controls the flow rate of the crude oil emulsion into the electrostatic desalter 2170 as well as allowing samples of the emulsion to be directed to the measurement station 2200. Measurements made on the solution samples would include but not be limited to impurity levels, temperature, amount of acid additive 2030 and wash water 2020 solution, etc. This information is sent to the controller 2110.

The electrostatic desalter 2170 includes a liquid level sensor (LS) 2210 used to measure the aqueous level in the electrostatic desalter 2170. In the embodiment of FIG. 2, the measurement output of the liquid level sensor 2210 is routed to the controller 2110. The controller 2110 uses the liquid level measurement data to control the controllable flow control valve 2220 to drain the effluent from the electrostatic desalter 2170 and control the aqueous layer and emulsion layer within the electrostatic desalter 2170. Alternatively, the liquid level sensor 2210 output may be directly connected to a level control valve instead of the controllable flow control valve 2220 to drain the effluent. The controllable flow control valve 2220 is also configured to allow samples of the effluent solution to be measured at a measurement station 2200. Measurements made on the solution samples would include but not be limited to solution pH, solution impurity levels, temperature, and amount of residual oil present in the effluent. This information is sent to the controller 2110.

The electrical power supply 2150 provides the voltage necessary to create the electric field necessary for electrostatic coalescence in the electrostatic desalter 2170. The controller 2110 controls the electrical power supply 2150 output. The electrical power supply 2150 output may be static (i.e. constant voltage with a current limit) or, preferably, able to change key parameters to enhance the desalting operation. The electrical power supply 2150 under the control of the controller 2110 would preferably be able to alter its' output to include but not be limited to changes in the voltage level applied to the electrostatic desalter 2170, the voltage waveform applied to the electrostatic desalter 2170, current limits (if any) on the electrical power supply 2150, or any combination thereof.

The desalted crude output of the electrostatic desalter 2170 passes through a pressure control valve 2180 and a controllable flow control valve 2190. The controllable flow control valve 2190 has two outputs to direct the desalted crude oil. Under control of the controller 2110, the controllable flow control valve 2190 controls and maintains the flow rate of desalted crude oil to the remaining refinery operations. Additionally, under control of the controller 2110, the controllable flow control valve 2190 can also direct samples of the desalted crude to the measurement station 2200. Measurements made on the solution samples would include but not be limited to impurity levels, temperature, residual acid additive 2030 and wash water 2020 solution, etc. This information is sent to the controller 2110.

The controller 2110 can adjust various factors of the desalting operation including but not limited to the following:

The crude oil supply 2010 feed rate through the controllable pump 2070 and controllable flow control valve 2120

The temperature of the crude oil supply 2010 through the controllable heater 2130.

Control of the dehydration mechanism 2310 water level and oil layers through the liquid level sensor 2340, the controllable flow control valve 2330, and the controllable flow control valve 2360.

The dehydration mechanism 2310 electric field through the controllable power supply 2300.

The solution mixture of acid additive 2030 and wash water 2020 through the controllable fluid mixer 2040.

The flow rate of the solution mixture of acid additive 2030 and wash water 2020 through the controllable pump 2050 and controllable flow control valve 2060.

The emulsion formation through controllable fluid mixer 2350.

The electrostatic desalter 2170 electric field through the controllable electrical power supply 2150.

Control of the electrostatic desalter 2170 water level and emulsion layers through the liquid level sensor 2210, the controllable flow control valve 2220, and the controllable flow control valve 2190.

As different tests are conducted with the desalting mechanism 2000, the parameters are adjusted per the test matrix and the selected product measurements are made after desalting the crude oil supply 2010. The memory/data storage 2100 function of the desalting mechanism 2000 allows the controller to access and update, if required, the control settings required to conduct the test matrix tests and store the measured data.

FIG. 3 shows a diagram of a typical two stage electrostatic desalting mechanism 3000 of the present invention.

The desalting mechanism 3000 of the present invention includes a crude oil supply 3010 for storing crude oil. The crude oil supply 3010 is connected to a controllable pump 3070 whose output is connected to a controllable flow control valve (FCV) 3120. The controllable flow control valve 3120 and the controllable pump 3070 work in conjunction under command of the controller 3110 to control and maintain the crude oil feed rate and pressure. The crude oil 3010 is heated to a desired processing temperature by the heater 3130 which is controlled by controller 3110. In the embodiment of FIG. 3, the heated crude oil is mixed with recycled effluent from the electrostatic desalter 3170 to create an emulsion mix of the crude oil supply 3010 and recycled effluent from the electrostatic desalter 3170 via the controllable fluid mixer 3380. Use of an effluent recycle as indicated in FIG. 3 is well-known in the art. The crude oil/effluent recycle emulsion passes through a pressure control valve 3160 before entering the electrostatic desalter 3310. The electrostatic desalter 3310 includes a liquid level sensor (LS) 3340 used to measure the aqueous level in the electrostatic desalter 3310. In the embodiment of FIG. 3, the measurement output of the liquid level sensor 3340 is routed to the controller 3110. The controller 3110 uses the liquid level measurement data to control the controllable flow control valve 3330 to drain the waste effluent from the electrostatic desalter 3310 and control the aqueous layer and emulsion layer within the electrostatic desalter 3310. Alternatively, the liquid level sensor 3340 output may be directly connected to a level control valve instead of the controllable flow control valve 3330 to drain the waste effluent. The controllable flow control valve 3330 is also configured to allow samples of the waste effluent solution to be measured at a measurement station 3200. Measurements made on the solution samples would include but not be limited to solution pH, solution impurity levels, temperature, and amount of residual oil present in the waste effluent. This information is sent to the controller 3110.

The electrical power supply 3300 provides the voltage necessary to create the electric field necessary for electrostatic coalescence in the electrostatic desalter 3310. The controller 3110 controls the electrical power supply 3300 output. The electrical power supply 3300 output may be static (i.e. constant voltage with a current limit) or, preferably, able to change key parameters to enhance the electrostatic coalescence operation. The electrical power supply 3300 under the control of the controller 3110 would preferably be able to alter its' output to include but not be limited to changes in the voltage level applied to the electrostatic desalter 3310, the voltage waveform applied to the desalter, current limits (if any) on the electrical power supply 3300, or any combination thereof.

The crude output of the electrostatic desalter 3310 passes through a pressure control valve 3320 on its way to the controllable fluid mixer 3350. The controllable fluid mixer 3350 allows a second emulsion of electrostatic desalter 3310 output, wash water 3020, and acid additive 3030 to be created based upon the specific characteristics of the crude oil supply 3010 to be desalted. The controllable fluid mixer 3350 is controlled by the controller 3110 to create and maintain the proper emulsion mix of crude oil 3010, wash water 3020, and acid additive 3030.

The desalting mechanism 3000 of the present invention also includes a wash water supply 3020 and an acid additive supply 3030. In the embodiment of FIG. 3, as is preferred, the acid additive 3030 is mixed with the wash water 3020 by the controllable fluid mixer 3040 before the crude oil/wash water emulsion is formed. Alternatively, the acid additive 3030 could be mixed with the wash water 3020 and crude oil 3010 during the emulsion creation or after emulsion creation or with the crude oil 3010 itself. The fluid mixer 3040 is controlled by the controller 3110 to create and maintain the proper solution mixture of acid additive 3030 and wash water 3020. The acid additive 3030 can be selected from the group consisting of oxalic acid, citric acid, glycolic acid, gluconic acid, C.sub.2-C.sub.4 alpha-hydroxy acids, malic acid, lactic acid, poly-hydroxy carboxylic acids, thioglycolic acid, chloroacetic acid, polymeric forms of the above hydroxyacids, poly-glycolic esters, glycolate ethers, and ammonium salt and alkali metal salts of these hydroxyacids, and mixtures thereof.

After mixing the solution of acid additive 3030 and wash water 3020 with the controllable fluid mixer 3040, the resulting solution is input to a controllable flow control valve 3090 which is used to allow samples of the mixed acid additive 3030 and wash water 3020 solution to be measured at a measurement station 3200. Measurements made on the solution samples would include but not be limited to solution pH, solution impurity levels, and percentage of acid additive 3030 to wash water 3020. This information is sent to the controller 3110.

After mixing the solution of acid additive 3030 and wash water 3020 with the controllable fluid mixer 3040, the resulting solution is also input to a controllable pump 3050 whose output is connected to a controllable flow control valve 3060. The controllable pump 3050 and the flow control valve 3060 work in conjunction under the command of the controller 3110 to control and maintain the wash water/acid solution feed rate and pressure. The output of the flow control valve 3060 is an input to the controllable fluid mixer 3350 where the second emulsion of electrostatic desalter 3310 output, wash water 3020, and acid additive 3030 is formed.

After mixing the second emulsion in the controllable fluid mixer 3350, the second emulsion passes through a controllable flow control valve 3360 before entering the electrostatic desalter 3170. The controllable flow control valve 3360, under command of the controller 3110, controls the flow rate of the second emulsion into the electrostatic desalter 3170 as well as allowing samples of the emulsion to be directed to the measurement station 3200. Measurements made on the solution samples would include but not be limited to impurity levels, temperature, amount of acid additive 3030 and wash water 3020 solution, etc. This information is sent to the controller 3110.

The electrostatic desalter 3170 includes a liquid level sensor (LS) 3210 used to measure the aqueous level in the electrostatic desalter 3170. In the embodiment of FIG. 3, the measurement output of the liquid level sensor 3210 is routed to the controller 3110. The controller 3110 uses the liquid level measurement data to control the controllable flow control valve 3220 to recycle the effluent from the electrostatic desalter 3170 and control the aqueous layer and emulsion layer within the electrostatic desalter 3170. Alternatively, the liquid level sensor 3210 output may be directly connected to a level control valve instead of the controllable flow control valve 3220 to recycle the effluent. The controllable flow control valve 3220 along with the controllable pump 3370, under command of the controller 3110, control and maintain the recycled effluent flow rate and pressure to the controllable mixer 3380. The controllable flow control valve 3220 is also configured to allow samples of the effluent solution to be measured at a measurement station 3200. Measurements made on the solution samples would include but not be limited to solution pH, solution impurity levels, temperature, and amount of residual oil present in the effluent. This information is sent to the controller 3110.

The electrical power supply 3150 provides the voltage necessary to create the electric field necessary for electrostatic coalescence in the electrostatic desalter 3170. The controller 3110 controls the electrical power supply 3150 output. The electrical power supply 3150 output may be static (i.e. constant voltage with a current limit) or, preferably, able to change key parameters to enhance the desalting operation. The electrical power supply 3150 under the control of the controller 3110 would preferably be able to alter its' output to include but not be limited to changes in the voltage level applied to the electrostatic desalter 3170, the voltage waveform applied to the electrostatic desalter 3170, current limits (if any) on the electrical power supply 3150, or any combination thereof.

The desalted crude output of the electrostatic desalter 3170 passes through a pressure control valve 3180 and a controllable flow control valve 3190. The controllable flow control valve 3190 has two outputs to direct the desalted crude oil. Under control of the controller 3110, the controllable flow control valve 3190 controls and maintains the flow rate of desalted crude oil to the remaining refinery operations. Additionally, under control of the controller 3110, the controllable flow control valve 3190 can also direct samples of the desalted crude to the measurement station 3200. Measurements made on the solution samples would include but not be limited to impurity levels, temperature, residual acid additive 3030 and wash water 3020 solution, etc. This information is sent to the controller 3110.

The controller 3110 can adjust various parameters of the desalting operation including but not limited to the following:

The crude oil supply 3010 feed rate through the controllable pump 3070 and controllable flow control valve 3120

The temperature of the crude oil supply 3010 through the controllable heater 3130.

Control of the electrostatic desalter 3310 aqueous level and emulsion layers through the liquid level sensor 3340, the controllable flow control valve 3330, and the controllable flow control valve 3360.

The electrostatic desalter 3310 electric field through the controllable power supply 3300.

The solution mixture of acid additive 3030 and wash water 3020 through the controllable fluid mixer 3040.

The flow rate of the solution mixture of acid additive 3030 and wash water 3020 through the controllable pump 3050 and controllable flow control valve 3060.

The first emulsion formation of crude oil supply 3010 and recycled effluent from electrostatic desalter 3170 through controllable flow control valve 3220, controllable pump 3370, and controllable fluid mixer 3380.

The second emulsion formation through controllable fluid mixer 3350.

The electrostatic desalter 3170 electric field through the controllable electrical power supply 3150.

Control of the electrostatic desalter 3170 water level and emulsion layers through the liquid level sensor 3210, the controllable flow control valve 3220, and the controllable flow control valve 3190.

As different tests are conducted with the desalting mechanism 3000, the parameters are adjusted per the test matrix and the selected product measurements are made after desalting the crude oil supply 3010. The memory/data storage 3100 function of the desalting mechanism 3000 allows the controller to access and update, if required, the control settings required to conduct the test matrix tests and store the measured data.

FIG. 4 shows an algorithm diagram for a multiple variable, two-level statistical quantification and estimation of performance for a given crude oil desalter 4000 according to one embodiment of the present invention.

In step 4010, the crude oil desalter for which performance will be characterized will be determined. The choice of crude oil desalter may be set based upon an existing refinery infrastructure. However, the company or processor who performs crude oil desalting may have a choice of desalting configurations. Thus, the processor may choose to conduct the multiple variable, two-level statistical quantification and estimation algorithm 4000 on more than one crude oil desalter configuration to choose the most economical configuration for processing a given crude oil type.

In step 4020, the desalter output product measurements to be characterized and modeled are chosen. The product measurements made for each test run may include but not be limited to the desalted crude oil salt content, basic sediments and water content of the desalted crude oil, the temperature of the desalted crude oil, the density of the desalted crude oil, the viscosity of the desalted crude oil, et al. Additionally, the costs to produce the desalted crude oil output product may also be collected for each test run.

In step 4030, the desalter parameters to be varied are chosen. The parameters to be varied for each test run may include but not be limited to the crude oil supply feed rate, the crude oil temperature, the electrostatic desalter aqueous layer, the electrostatic desalter emulsion layer, the electrostatic desalter electric field, the demulsifier type, the pH of the acid additive and wash water solution, and/or the flow rate of the acid additive and wash water solution.

In step 4040, a minimum and maximum setting are chosen for each variable selected in step 4030. The minimum and maximum setting should be at the limits that would be used in a potential desalting application. Additionally, for the multiple variable, two-level statistical quantification and estimation algorithm 4000, the minimum and maximum for each variable should be chosen such that the expected effect on the product output is linear over the minimum and maximum setting range. The multiple variable, two-level statistical quantification and estimate of performance technique 4000 can be extended to multiple min/max ranges to estimate performance in a piece-wise linear estimate for situations with intrinsically high non-linearity over an extended parameter range.

In step 4050, the 2-level test matrix is designed. The matrix identifies the parameter settings for all of the test combinations. Each parameter is set to one of the two ranges chosen in step 4040 for each test run. In the initial 2-level test matrix design of step 4050, all combinations of parameter settings are tested so that all possible effects, including parameter interactions, are independently estimated. As an example, the test matrix developed in step 4050 would be represented by Table I if we were measuring the cost of desalting a certain number of barrels of crude oil while varying three desalting parameters between two levels; the pH of the wash water and acid additive solutions (designated as parameter A), the temperature of the crude oil (designated as parameter B), and the crude oil flow rate (designated as parameter C).

TABLE I
Step 4050 Example 2-Level Test Matrix for Three Parameters
	Test Run	A	B	C
	1	L	L	L
	2	L	L	H
	3	L	H	L
	4	L	H	H
	5	H	L	L
	6	H	L	H
	7	H	H	L
	8	H	H	H

where represents the parameter set at the minimum value and ‘H’ represents the parameter set at the maximum value.

The number of effects that can be modeled for the design of step 4050 is given by 2^m-1 where m is the number of parameters to be varied. The prediction estimate resulting from the 2-level test matrix design of step 4050 is an approximation of the process response model to the parameter variations and is given by equation 1 (eq. 1), below,

$\begin{array}{cc}\hat{Y}=\stackrel{\_}{Y}+\sum _{i=1}^mn_ix_i+\sum _{i=1}^{m-1}\sum _{j=i+1}^mn_{\mathrm{ij}}x_ix_j+\sum _{i=1}^{m-2}\sum _{j=i+1}^{m-1}\sum _{k=j+1}^mn_{\mathrm{ijk}}x_ix_jx_k+\dots \mathrm{higher}\mathrm{order}\mathrm{terms}\mathrm{as}\mathrm{applicable}& \mathrm{eq}.1\end{array}$

where Ŷ is the output estimate, Y is the average of the outputs from all test matrix runs, n represents the coefficients for each model term, and x_i represents the variable parameters.

Step 4060 computes the total number of tests that must be conducted. The total number of tests is given by the number of test runs times the number of tests per test run. In step 4110 a hypothesis test is conducted to determine the significance of each term in the prediction estimate developed in step 4050. The number of tests per test run may be computed based upon the statistical confidence that each term placed in the prediction equation is significant coupled with minimizing the possibility that a significant term is determined to be insignificant. The number of test runs is determined by the test matrix design.

Decision step 4080 determines if the total number of tests is acceptable. This decision considers the resources required to conduct each test, the estimated total expense, the time that will be required to run the tests, etc.

If the total number of tests is determined to be too high, the number of tests is reduced in step 4070. The total number of tests may be reduced by re-designing the test matrix, reducing the number of tests per test run, or both. If the test matrix is re-designed to eliminate test runs, there will be one or more terms eliminated in the prediction equation as a result. The choice of term to eliminate is based upon the likelihood that the term is significant. The impact of eliminating the term(s) in the prediction equation is that the design will have one or more terms ‘aliased’ with the eliminated term. The practical implication of aliasing is that it will not be possible to determine whether an output effect is due to a lower order term, the eliminated term, or some combination of both. Generally, higher-order terms may be eliminated in a test matrix re-design while the main effect terms and lower order interaction terms are preserved. In a re-designed test matrix, it is desirable that the resulting test matrix does not alias the main effect terms

$\left(\sum _{i=1}^mn_ix_i\right)$

with each other or with two-way interactions

$\left(\sum _{i=1}^{m-1}\sum _{j=i+1}^mn_{\mathrm{ij}}x_ix_j\right).$

In addition, it is desirable that the two-way interactions are not aliased with one another.

In step 4090, the tests are conducted for each test run. It is desirable to run the tests in a random order to help compensate for minor variation in uncontrolled parameters. For each test conducted in step 4090,

The variable process characteristics are set to the min or max value based upon the test run to be conducted.

An acid additive is mixed with wash water, directly with the crude oil, or a wash water/crude oil solution.

An emulsion of acid additive, wash water, and crude oil is created

The wash water/acid additive/crude oil emulsion is resolved into an oil phase and aqueous phase.

The output response characteristics are measured and recorded for the applicable test run.

In step 4100, a series of statistical computations are made on the data collected in step 4090. To facilitate the computations to be made in step 4100 and step 4110, the test matrix parameter variations between the minimum and maximum are transformed using the following equation (eq. 2):

$\begin{array}{cc}{\mathrm{CS}}_i=\frac{2\times \left({\mathrm{AS}}_i-{\stackrel{\_}{\mathrm{AS}}}_i\right)}{{\mathrm{Max}}_i-{\mathrm{Min}}_i}& \mathrm{eq}.2\end{array}$

where CS_i is the coded setting for parameter i, AS_i is the actual setting for the parameter i, AS_i is the average of all the actual settings for parameter i, Max, is the maximum actual setting for parameter i, and Min_i is the minimum actual setting for parameter i. The actual parameter settings are used during the test runs, the coded parameter settings are used for analysis purposes. Using the transformation defined by eq. 2, when evaluating eq.1, each parameter setting would be defined by its coded value. For the example defined to develop Table I, the coded test matrix values for each candidate variable in the prediction equation would be represented by Table II.

TABLE II
Example 2-Level Coded Test Matrix for Three Parameters and
All Interactions
	Test
	Run	A	B	C	AB	AC	BC	ABC
	1	−1	−1	−1	+1	+1	+1	−1
	2	−1	−1	+1	+1	−1	−1	+1
	3	−1	+1	−1	−1	+1	−1	+1
	4	−1	+1	+1	−1	−1	+1	−1
	5	+1	−1	−1	−1	−1	+1	+1
	6	+1	−1	+1	−1	+1	−1	−1
	7	+1	+1	−1	+1	−1	−1	−1
	8	+1	+1	+1	+1	+1	+1	+1

For each test, run in the test matrix compute the average output response as (eq. 3)

$\begin{array}{cc}\stackrel{\_}{y_{\mathrm{tr}}}=\sum _{i=1}^n\frac{y_i}{n}& \mathrm{eq}.3\end{array}$

where y_tr is the average output response of each test run, y_i is the output response for each test for the test run, and n is the number of tests conducted per test run.

For each test run in the test matrix, the sample variance is also computed as (eq. 4)

$\begin{array}{cc}{V}_{\mathrm{tr}}=\sum _{i=1}^n\frac{{\left(y_i-\stackrel{\_}{y_{\mathrm{tr}}}\right)}^2}{\left(n-1\right)}& \mathrm{eq}.4\end{array}$

where V_tr, is the variance of the output responses for each test run, y_tr is the average output response of each test run, y_i is the output response for each test for the test run, and n is the number of tests conducted per test run.

For each candidate variable in the prediction equation, the difference in the average output response between the maximum settings for the variable (i.e. coded value of +1) and the minimum settings for the variable (i.e. coded value of −1) is computed as (eq. 5)

y_i= y₊− y₋  eq. 5

where y_i represents the difference in the average output response between the maximum setting and minimum settings for the candidate variable i, y₊ is the average output response for all test runs in which the candidate variable i has a coded value of +1, and y₋ is the average output response for all test runs in which the candidate variable i has a coded value of −1.

In step 4110, a statistical hypothesis test is conducted for each candidate variable in the prediction equation to determine if the candidate variable has a statistically significant contribution to the output response. There are many statistical methods of hypothesis testing. In the embodiment of the present invention, hypothesis testing for the multiple variable, two-level statistical quantification and estimation of performance for a given crude oil desalter 4000 will utilize the F distribution.

The hypothesis to be tested can be defined for each candidate variable in the prediction equation as:

H₀: The average output response for +1 coded values is statistically equal to the average output response for −1 coded values. Therefore, the candidate variable does not significantly contribute to the output response.

H₁: The average output response for +1 coded values is statistically different from the average output response for −1 coded values. Therefore, the candidate variable does significantly contribute to the output response.

These two statements are called the null hypothesis (H₀) and the alternative hypothesis (H₁). There are two errors that may be made in the hypothesis test. The first error, called a Type I error, is concluding that the alternative hypothesis is true when in fact the null hypothesis is true. The second error, called a Type II error, is concluding that the null hypothesis is true when in fact the alternative hypothesis is true. In step 4110, the probability of committing a Type I error (a) is chosen for each candidate variable in the prediction equation.

For each candidate variable, the mean-square-between value is computed in step 4110 as (eq. 6)

$\begin{array}{cc}{\mathrm{MSB}}_i=\frac{N}{4}\times {\left(\stackrel{\stackrel{\_}{\_}}{y_i}\right)}^2& \mathrm{eq}.6\end{array}$

where MSB_i is the mean-square-between value for the candidate variable i, N is the total number of tests conducted in step 4090 (number of test runs times the number of tests per test run), and y_i is the difference in the average output response between the maximum setting and minimum settings for the candidate variable i computed using eq. 5 in step 4100.

For each candidate variable, the mean square error is computed in step 4110 as (eq. 7)

$\begin{array}{cc}\mathrm{MSE}=\frac{\sum _{\mathrm{tr}=1}^k\left(n-1\right)\times V_{\mathrm{tr}}^2}{\sum _{\mathrm{tr}=1}^k\left(n-1\right)}& \mathrm{eq}.7\end{array}$

where MSE is the mean square error, k is the number of test runs, n is the number of tests per test run, and V_tr is the variance of the output responses for each test run.

In step 4110, the MSE and MSB_i are both estimates of the population variance and should be approximately equal in value if the null hypothesis is true. It is likely that the MSE and MSB_i will not be exactly the same since they are estimates that are based upon different aspects of the sample statistics (MSB_i is computed from the sample means and MSE is computed from the sample variances). However, if the alternative hypothesis is true, the MSB_i will compute to a larger value due to the differences among sample means while the MSE will still estimate the population variance because differences in population means do not affect variances. Thus, to determine the statistical significance of a candidate variable in eq.1, the associated mean-square-between value is compared to the mean square error in the form of an F ratio. The F ratio to be computed for each candidate variable in step 4110 is given by eq. 8

$\begin{array}{cc}{F}_i=\frac{{\mathrm{MSB}}_i}{\mathrm{MSE}}& \mathrm{eq}.8\end{array}$

where F_i is the F ratio for the candidate variable i, MSB_i is the mean-square-between value for the candidate variable i, and MSE is the mean square error.

In step 4110, each F_i is compared to the F-statistic which depends upon the significance level (1-α), the degrees of freedom for the mean-square between value (equal to one for two-levels), and the degrees of freedom for the mean square error (equal to

$\sum _{\mathrm{tr}=1}^k\left(n-1\right)$

in eq. 7). If F_i is less than or equal to the F-statistic, then the alternative hypothesis is rejected and the candidate variable i in eq.1 is not considered significant. If F_i is greater than the F-statistic, then the null hypothesis is rejected with (1-α)100% confidence and the candidate variable i in eq. 1 is considered significant. It should be noted that Y, which is the average of the outputs from all test matrix runs, is not tested for significance and is included in the prediction estimate of eq. 1. For each candidate variable i in eq.1 that is considered significant, the coefficient for the model term, n_i, is given by eq. 9

$\begin{array}{cc}{n}_i=\frac{\stackrel{\stackrel{\_}{\_}}{y_i}}{2}& \mathrm{eq}.9\end{array}$

where n_i is the model term coefficient for the significant candidate variable i and y_i represents the difference in the average output response between the maximum setting and minimum settings for the candidate variable i.

In step 4120, the prediction equation (s) resulting from step 4110 is used to predict the response for various parameter settings. If the objective is to minimize or maximize the output responses, the optimum settings may be obtained using the associated prediction equations. It should be noted that the values for the significant parameters in the prediction equation must be in coded form (i.e. between −1 and +1). The parameter setting may be transformed from a coded value to an actual setting using the following calculation (eq. 10)

$\begin{array}{cc}{\mathrm{AS}}_i=\frac{{\mathrm{CS}}_i\times \left({\mathrm{Max}}_i-{\mathrm{Min}}_i\right)}{2}+\stackrel{\_}{{\mathrm{AS}}_i}& \mathrm{eq}.10\end{array}$

where CS_i is the coded setting for parameter i, AS_i is the actual setting for the parameter i, AS_i is the average of all the actual settings for parameter i, Max, is the maximum actual setting for parameter i, and Min, is the minimum actual setting for parameter i.

After the parameter settings have been optimally computed using the prediction equation, a number of tests may be conducted in step 4120 with the optimally computed settings to determine if the response output statistically agrees with the predicted output.

In decision step 4130, it is determined if more tests are necessary to refine the prediction equation. This decision is driven by the confidence level desired for each variable in the prediction equation coupled with the results of testing in step 4120, if any. If additional tests are determined to be necessary, the computed prediction equation is discarded and additional tests are conducted in step 4090. If there are no additional tests deemed necessary, the prediction equation developed in step 4110 and optimized in step 4120 is considered confirmed.

FIG. 5 shows a process diagram 5000 of one embodiment of the method of the present invention for a typical crude oil desalting operation.

In step 5010, the crude oil desalter configuration is determined. The configuration may be a single stage electrostatic desalting mechanism, a first stage dehydration followed by a second stage electrostatic desalting mechanism, a two stage desalting mechanism, or any other form of crude oil desalting mechanism.

In step 5020, the output response characteristics to be modeled and measured are selected. Output response characteristics that may be selected include but are not limited to the desalted crude oil impurities, the percentage of basic sediments and water of the desalted crude oil, and/or the cost to desalt the oil. One or more of the selected characteristics may be measured for each test run. Each different output response will have a corresponding prediction equation model associated with it.

In step 5030, the process characteristics to be varied are selected along with the minimum and maximum variation levels. The crude electrostatic desalter characteristics that may potentially be varied include but are not limited to the crude oil feed rate, the crude oil temperature, the dehydration/desalter electric field characteristics, the wash water flow rate, the emulsion formation, the control of the dehydration/desalter water level and emulsion layer, the acid additive type, the acid additive rate, and the effluent recycle.

In step 5040, the appropriate statistical test matrix design is determined based upon the number of parameters to be varied, the number of levels of variation, and the number of tests to be conducted per test matrix run. The result of this step determines the total number of tests to be conducted and the potential parameter interactions where prediction aliasing may occur.

In step 5050, the tests are conducted. Preferably, the tests are run in random order relative to the test matrix. For each test, the following steps are made:

The variable process characteristics are setup according to the selected test matrix run.

An acid additive is mixed with the wash water, directly with the crude oil, or with a wash water/crude oil solution.

An emulsion of acid additive, wash water, and crude oil is created.

The crude oil is resolved into an oil phase and an aqueous phase.

The chosen output response characteristics are measured.

In step 5060, an equation or series of equations relating the output responses selected in step 5020 to the process characteristics selected in step 5030 is developed. The equation (s) are based upon the statistical computations made on the data collected in step 5050 relative to the variation in the process characteristics. The variables in the developed equations are determined to be statistically significant with a (1-α)100% confidence level Where α is selected before step 5060 is conducted.

In step 5070, the prediction equation is optionally confirmed through a series of experiments.

The above embodiments are merely preferred and the scope of the invention defined by the claims below.

The method can be performed, by an oil refinery, desalter, or laboratory equipment.

Claims

1. A method for removing calcium, iron, other metals, and amines from crude oil in a refinery desalting process comprising the steps of:

running a plurality of tests to determine at least one statistically significant processing characteristic of the refinery desalting process;

adding a wash water to the crude oil;

adding the wash water to the crude oil to create an emulsion;

adding to the wash water, the crude oil or the emulsion an acid additive consisting of at least one of the following: oxalic acid, citric acid, water-soluble hydroxyacid selected from the group consisting of glycolic acid, gluconic acid, C.sub.2-C.sub.4 alpha-hydroxy acids, malic acid, lactic acid, poly-hydroxy carboxylic acids, thioglycolic acid, chloroacetic acid, polymeric forms of the above hydroxyacids, poly-glycolic esters, glycolate ethers, and ammonium salt and alkali metal salts of these hydroxyacids, and mixtures thereof;

resolving the emulsion containing the acid additive into a hydrocarbon phase and an aqueous phase; and

adjusting a control setting of the processing characteristic as a function of the tests.

2. The method as recited in claim 1 wherein the pH of the wash water, if the hydroxyacid is added to the wash water, is below 6.

3. The method as recited in claim 1 wherein different control settings are stored for different types of crude oil.

4. The method as recited in claim 1 wherein the tests include a plurality of candidate variables representing different processing characteristics.

5. The method as recited in claim 4 wherein the tests include setting minimum and maximum values for the candidate variables.

6. The method as recited in claim 1 wherein the hydroxyacid selected is malic acid.

7. The method as recited in claim 1 wherein the processing characteristic is a temperature of the crude oil or wash water.

8. The method as recited in claim 1 wherein the processing characteristic is a crude oil supply feed rate.

9. The method as recited in claim 1 wherein the processing characteristic is a temperature of the emulsion.

10. The method as recited in claim 1 wherein the processing characteristic is a percentage of hydroxyacid additive to the wash water.

11. The method as recited in claim 1 wherein the processing characteristic is a flow rate of a solution mixture of hydroxyacid additive and wash water.

12. The method as recited in claim 1 wherein the processing characteristic is an electrostatic desalter electric field.

13. The method as recited in claim 1 wherein the processing characteristic is an electrostatic desalter water or emulation level.

14. The method as recited in claim 1 further comprising determining a prediction equation as a function of the tests.

15. The method as recited in claim 4 wherein a mean square function determination is made for each candidate variable.

16. A method for improving a refinery desalting process comprising the steps of:

providing a range of values for at least one candidate variable representing a desalting process characteristic;

performing a statistical calculation to determine at least one statistically significant candidate variable of the at least one candidate variable which is statistically significant for improving the refinery desalting process; and

adjusting a control setting of the desalting process as a function of the statistical calculation.

17. The method as recited in claim 16 wherein the range of values includes a minimum value and a maximum value.

18. The method as recited in claim 16 wherein the at least one candidate variable includes a plurality of candidate values.

19. A crude oil refinery, crude oil desalter, or laboratory environment operating the method as recited in claim 1.

20. A crude oil refinery, crude oil desalter, or laboratory environment operating the method as recited in claim 16.