IPTC-17413-MS..ESP

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ESP Well Surveillance using Pattern Recognition Analysis, Oil Wells,Petroleum Development OmanA. Awaid, H. Al-Muqbali, A. Al-Bimani, Z. Al-Yazeedi, H. Al-Sukaity, K. Al-Harthy Petroleum Development Oman;Alastair Baillie Engineering Insight Ltd, Aberdeen

Copyright 2014, International Petroleum Technology Conference

This paper was prepared for presentation at the International Petroleum Technology Conference held in Doha, Qatar, 2022 January 2014.

This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, aspresented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarilyreflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committeesof IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference isprohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment ofwhere and by whom the paper was presented. Write Librarian, IPTC, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax +1-972-952-9435

Abst ract

PDO is managing some 850 Electrical Submersible Pump (ESP) systems scattered across North & South fields,which is continue to grow in the next five years business plan. All ESP wells have real time down-hole sensors thatmeasures intake and discharge pressures, intake and motor temperatures, vibration and current leakage. The oilproducing fields are equipped with real time data transmission system where several data measurements; downhole (such as pump intake and discharge pressures and temperatures) and surface (such as volts, amps andfrequency) are transmitted directly from the well site to the gathering stations, central control rooms and even tothe engineers desktop.

At present, PDO is deploying an integrated smart tool which will monitor, control, and optimize oil production andESP performance to the various disciplines involved in oil production and optimization like Reservoir andPetroleum Engineers, Programmers, and Field Operation Teams. However, in order to enable these modern wellsurveillance systems, which often produce an overwhelming quantity of information but the data is often misleadingor difficult to interpret, establishing the Pattern recognition of the trended real time data is key to make the softwareintelligent enough to be effective to the work places.

This paper will demonstrate how precise ESP, well and reservoir performance can be predicted from simplephysical relationships and how these relate to the trends of surface and downhole data. A number of real fieldexamples of data trends will be shown to illustrate how a proper understanding of these patterns will allow promptESP troubleshooting and ensure the correct actions are taken. The results are correlated with equipment pull andinspection reports to validate the diagnosis.

Pattern recognition trends and analysis will be presented for common problems such as hole in tubing, shut in at

surface, ESP wear, blockage at pump intake, debris in pump, broken shaft, change in reservoir pressure, blockageat perforations, etc. A proper understanding of these trends will allow the correct settings of alarm and trips andassist in the implementation of semi-automated well surveillance and diagnostic system which being currentlydeployed in the Company. A pattern recognition analysis check sheet will be included in the paper to allow users toquickly interpret data trends and diagnose well, ESP and reservoir performance problems.

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Introduction

PDO is operating some 850 ESPs in various fields across PDO concession area. The ESPs population iscontinuing to grow in the next 5 years as indicated in the companys Business Plan.

Fields / Wells BackgroundThe ESP fields are varied in term of reservoir type, fluid type, production range, production reservoir mechanisms,

well construction & completion schemes, etc.

In the North, the ESP fields are mainly carbonates reservoirs and are produced with water flood. The produced oilis mainly light (30 to 40 API); medium to high gross rate (up to 1400 m3/d) at high water cut (up to 96%). The newfields are cutting high net oil (0 to 20% BSW) at medium gross rates (up to 600 m3/d). The wells are completed asvertical, horizontal and even multilateral wells normally single zones.

In the South, the ESP fields are mainly sandstones and the wells are completed with sand control. The productionis mainly on depletion drive, with the old filed cutting high water cut (up to 96% BSW). The wells are producingmedium gross rate (up to 800 m3/d). The wells are completed as vertical and horizontal wells with some layerscommingled.Surveillance using current set-up

It is very common in PDO to monitor, analyze & diagnostic ESP wells using measured real time surface &

downhole data. The routine ESP surveillance fosters to work efficiently & enhance understanding of the ESPperformance as well as reservoir behaviors.

Real time data and Monitoring

Acquisition Down-Hole: All the ESPs wells are equipped with down- hole sensors mainly of enhanced type whichmeasures Intake Pressure (Pi); Discharge Pressure (Pd); Motor Winding Temperature (Tm); Pump IntakeTemperature (Tpi)

Acquisition Surface: Each well has a transducer at the Well Head to measure Tubing Head Pressure. The CasingHead pressure is measured at A annulus by another transducer.

Flow system:The production is measured mainly by three or two Phase Separators. In some remote fields / newsmall fields, mobile production meters are used and in some cases a Well Test Unit is used to measure the

production (Gross liquid rate; Oil rate; produced Gas rate. Well Head samples are taken routinely to measure BSWand calibrate water cut.

SCADA System:All PDO wells are connected at real time to readsurface & downhole data of wells, facilities andstations including production data. Data are thensent to the Remote Terminal Unit (RTU) which inturn sends the data using wireless technology to theFieldware (now uploaded to LOWIS to some of thewells/fields) server in the field. Figure 2 belowshows the different stages that data goes throughfrom the source to the user.Ref.1

Figure 1

Integrated well system surveillance tool in use [ LOWIS / NIBRAS ]

SHUROOQ:This in-house web based system which captured and present all the real time data of wells, facilities & stationswhich can be accessed anywhere across Company server. The data is mainly displayed by trending.All wells havereal time trending plots while for ESP wells, a more detail downhole data are displayed for a thorough ESPanalysis & diagnostic. Shurooq will be superseded by NIBRAS.

NIBRAS (will supersede Shurooq):

RTU RTU RTU

Corp DBs

& SAP PI

FieldBus Control

System

RPC RPC MFM

FieldWare and RT Applications

Shurooq .NET Web Server

WEB

ESPs, GL, WI, PCP Wells

OPC-PI direct link

Production

DB

OPC Layer OPC Layer OPC Layer OPC Layer OPC LayerOPCOPCOPC

BeamLiftWells

RTU RTU RTU

Corp DBs

& SAP PI

FieldBus Control

System

RPC RPC MFM

FieldWare and RT Applications

Shurooq .NET Web Server

WEB

ESPs, GL, WI, PCP Wells

OPC-PI direct link

Production

DB

OPC Layer OPC Layer OPC Layer OPC Layer OPC LayerOPCOPCOPC

BeamLiftWells

RTU RTU RTU

Corp DBs

& SAP PI

FieldBus Control

System

RPC RPC MFM

FieldWare and RT Applications

Shurooq .NET Web Server

WEB

ESPs, GL, WI, PCP Wells

OPC-PI direct link

Production

DB

OPC Layer OPC Layer OPC Layer OPC Layer OPC LayerOPCOPCOPC

BeamLiftWells

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Is an in-house web-portal based tool, a smart platform for Well & Reservoir Management (WRM).The tool functionsincludes the standard data sources, web-accessibility, multi-levels of data presentation, exception-basedsurveillance and it is compatible with third-party tools. Hence NIBRAS, to some degree, can be able to identify well& reservoir related issues earlier for an optimum decision. The idea of NIBRAS is to integrate the all PDO Assetsthus by bringing consistency across the Company in retrieving data from different sources, and in presenting data(pressure and production; surface & downhole) in different formats. The tool does not possess capability of NodalAnalysis, hence it remain as a data trending tool.

LOWIS (eventually, once fully capable, will supersede FieldWare):Is a web-based well management software, designed to help improve integrated monitoring and optimization for oiland gas production operation. The tool architecturally aimed to integrate and optimize workflows for optimummonitoring & optimization. Fieldware is being replaced with LOWIS tool.

How we identify the ESP problems

In PDO, main failure types are categorized into the following groups:

i. Equipment relatedii. Well condition relatediii. Unknown: those which either still under investigation / discussion or are difficult to be categorized due to the

lack of the information.

PDO failure notification process:

Each major field or a group of fields is equipped with Computer Control rooms (CCR) which display all the wells atreal time status around the clock where any abnormality is notified and attended accordingly. Once the controlrooms Identify trips, the action on verification & trouble shooting is started.

1. Verify and confirm the trip.

The trips setting values are checked & verified if are still applicable at the current time. Trips parameterswhich are common used in ESPs are: Overload / Under load current; Current Imbalance; Over / Undervoltage; Voltage Unbalance & surface Pressures (THP; F/L P) and Subsurface Intake Pressure & MotorTemperature. Appendix 1 gives the details of Trip settings & values.

.2. Trouble shooting by ESP vendor at well site.

The CCR technician / Production Supervisor will notify the ESP Vendor to physically check the ESP Wellwhen the well stops producing. The trouble shooting activity can be as simple as re-adjust the Alarm settingsto back flush through the casing Annulus to Tubing or rock the well, re-configure the Controller, etc. Sometripped ESP wells can be recovered and some have to be worked over. There are times, the complex trips willmiss the opportunity to be recovered due to the well site competence. In addition, it is vital to have competentpersonal field support to avoid un-necessary trips which eventually could end up on failures.

3. Confirm ESP failure.

ESP vendor has to inform the CCR / Production Supervisor that the ESP is confirmed failed. Average daystaken on this step of the Process can be from 1 to one week. Although the real time trend is normally used

alongside other surface measured parameters in investigation, but in some cases, the analysis becomeinconclusive, and the trouble shooting activity takes longer time than expected with additional acticitivities tothe wells / surface ESP facility such as back flush, hard start; etc.

4. Types of failures:

In most cases, one of the pre-pull activities will be the trouble shooting in attempt to recover the tripped ESPwell. In case of un-successful trouble shooting, the tripped ESP will be confirmed a failure where will becategorized as either Mechanical or Electrical except if it has clear evidence of Hole in the Tubing. If still thereis no clear evidence of pin point the failure code upon pull out of hole, the failure codes remain as Mechanicalor Electrical. Although well condition can be easily related to many failures, but the root cause of failure canonly be confirmed after a DIFA analysis.

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Figure 2 Figure 3

Why we need Pattern Recogn ition analysisWhen we look the historical trend of ESPs failures, the majority of the failures are repetitive; it is well known thatmost of the observed ESPs failures have been seen in the past. We are still spending a tremendous time (days toa week) to confirm a failure or in some cases to even differentiate between a failure and a trip. By developing anagreed analytical technical and mathematical tested Pattern to all the common failures and trips in PDOs ESPoperation, the failures will be identified and even be able to be predicted faster for a quick reaction and optimumsolution. In addition, pattern Recognition will enable the engineers to monitor huge data in a particular field for agroup of wells.

As it can be seen, the ESP failures are repetitive at increasing trend in some cases. The Pattern Recognitionanalysis will enable to pin point the abnormal ESP operation case prior to trips or failures. In addition, this level ofanalysis will assist in clarifying the trips / failure reason for a fast reaction thereby minimizing downtime andassociated oil deferment.

Figure 4 Figure 5

Armour

washed out,

high pressure

gas ingress inImpeller full

of scale

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Is there any tool to predict the failure? Can Pattern Recognition support the effort?

There are tremendous efforts worldwide from Operating Companies to Service Companies in establishing anddeveloping a failure predicting tool through various approach, such as statitisticaly; technically; analytically, etc.

As the failures are repeating, and with the vast real time data, the failure can be predicted through ESP EBSapproach once the Pattern Recognition analysis cases have been tested using Nodal Analytical Tools while crosschecking with the Real Time trend, the common trips and failures can be predicted for pro active trouble shootingand remedial work.

Common ESP cases (can be failure causes)

During ESP operations, there are a number of changes can happen downhole or at surface which can disturb thenormal operation of ESP which at the end can cause a trip or failure. These changes can be mechanically;hydraulically or electrically, and can be at the surface; in the tubing / ESP equipment or even in the reservoir.Some of these deviations can actually improve the ESP performance in term of production. After operating thesefields for many years with the same reservoirs and fluid characteristics; and after experiencing various types offailures while matching with the real time data trending, the Pattern was derived from various common cases.

Pattern Recognition Cases

PDO have identified 13 cases which can derive a specific unique pattern in term of the change of the measuredparameters (variables) which can be used to analyze the ESPs as part of ESP diagnosis. These identified patterncases are listed as follow:

1. Broken shaft2. Hole in Tubing3. Blockage at Pump Intake4. Blockage at Perforations5. Increase in Water Cut6. Shut in at Surface

7. Blockage in Pump Stages8. Increase in Reservoir Pressure9. Increase of free gas at Pump Intake10. Wearing Stages (erosion)11. Increase in Frequency12. Open Choke (decrease in WHP)

The analysis and diagnosis of four of the above cases will be discussed using its Pattern Recognition frommeasured variables in Shurooq trending; while matching with Gradient Traverse Plot and Pump Curve from WellModels. In addition, each case, where possible, will be cross checked with the results during Pull out of Holes orRoot Cause Analysis (RCA) to support the Pattern Recognition.

How to diagnose ESP using Pattern Recogni tion Analysis

How it all started

In 2011 / 2012, PDO conducted a series of ESP on the Job Training at Level 1 and Level 2. The Level 1 wasattended by Petroleum Engineers, Operation Engineers, Field Production Engineers, some Well Engineers andReal Time Operation. The course focuses on ESP Systems Designs, Diagnosis and Optimization.

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Upon completion of Level 1, a small group of participants attended Level 2 where the focusing was more onadvanced ESP systems Modeling and Analysis using Nodal Analysis software and in house real time data trendingweb base system. The Advanced Level 2 courses, done as a workshop, was to build on the basic principles ofProsper modeling and Shurooq surveillance in order to develop, analyse and troubleshoot more complex modelsor situations and to share this knowledge amongst the various PDO assets. In these Level 2 Workshops, theparticipants were able to apply the ESP basic concepts learned from Level 1 to well and ESP models while using

the real time data trending.

In the Level 2 workshops, after analyzing various real time example cases, the participants together with the ESPConsultant (Course Instructor) and PDO ESP SME were able to build the Pattern for each case by testing eachmeasured variables, which was then developed as a Pattern Recognition Checklist. The Pattern for some caseswas tested by the Nodal Analysis software to analyze the Pressure behavior on Pressure Gradient plot & analyzingthe Operating Point on Pump curve plot..ESP Wells Diagnosis - Pattern Recognition

An ESP well can be easily and quickly diagnosed by following the logical flow of the equations given. It isimportant to ensure the below simple logic is followed during the diagnoses stage:

- Above the pump- Across the pump- Below the pump- Reservoir

1) Above the pump (wellhead to pump):

Pdischarge= WHP + Pgravity + Pfriction

Fluctuations in Pdischargeare the results of changes in:

- WHP- Mixture density in the tubing (i.e. gas or water cut)- Fluid level in the tubing (TVD)- Flow rate, tubing diameter change

2) Across the pump:

Pintake = Pdischarge- Ppump

where Ppump = Head (ft) x Mixture Density (psi/ft)

and Head depends on: flowrate(inverse relationship)rpm

2

size and type of impellergas (cavitation)viscosityblockage in stages (sand/debris etc.)reverse rotation

3) Below the pump (pump to reservoir):

Pwf = Pintake+ Pgravity + Pfriction

Variations in Pwfwill affect flow from the reservoir.

Note that Ppump friction is normally small or zero (casing)

4) Reservoir:

Q = PI (PR- Pwf) (reservoir inflow performance)

Validates:reservoir inflow performance, flowrate, PI, PR.

Pgravity (~95%)

Pfriction (~5%)

Normal

Adverse

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Basic technical concept of ESP

As discussed on the equations above, an ESP well can be easily and quickly diagnosed by following the logicalflow of the equations, which is now is given on Pressure Gradient plot. While applying the equations, follow thelogic above the pump; across the pump; below the pump and at reservoir.

The key in the ESP diagnosis is one should not jump to conclusion and start using a gut reaction! For example, ifduring ESP diagnosis one has a doubt about flowrate, then need to check with the reservoir (check drawdown).Using this process, the behavior of a well can be predicted for any set of conditions.

:

The variables that can be predicted are as follows

- Flowrate

- WHP

- Amps

- Pdischarge

- Pintake

- Pump dP

- Motor temperature

Depth(TVD)

Pressure PR

Pd

WHP

Abovepump

Pi

Across pump

P

BelowpumpDrawdown

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Pattern recognit ion analysis check sheet

Using the physical relationships contained in the equations given above, specific combinations of surface anddownhole parameters can be used to describe any change of reservoir, well or ESP performance. These areshown in the check sheet below (Table 1).

1) Broken shaft 7) Blockage in pump stages2) Hole in tubing 8) Increase in reservoir pressure3) Blockage at pump intake 9) Increase of free gas at pump intake4) Blockage at perforations 10) Wearing stages (erosion)5) Increase in watercut 11) Increase in frequency6) Shut in at surface 12) Open choke (decrease in WHP)

The arrows indicate the rate of change of the variable. The coloured boxes indicate the unique characteristics ofthe response. The best trip parameters are indicated by .TRIP

Table 1: Pattern Recognit ion Analysis checklist

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Field Test to Confirm s imilar response Cases

It is worth mentioning that the following three cases show quite similar responses:

Hole in tubing

Blockage at pump intake

Blockage in pump stages

These can be differentiated by the following physical tests in the field:

1) Pressure test tubing

Install plug in nipple or profile immediately above pump and pressure test with water. This test will immediatelyidentify a hole in the tubing (but not hole in pump section)

2) Shut at surface (short duration 5 minutes)

Observe WHP, Ppumpand Amps.

A hole in tubing should show a small increase in WHP, little or no change in Ppump or amps.The volume of fluid circulating around the pump will not change during a surface shut-in, so the operating point on

the head (Ppump) and load curve (amps) will not change.

The blockage at pump intake should give the highest WHP and Ppumpand a decrease in amps.The pump itself (impellers and diffusers) are not damaged in this case and so the pump should still generate the

maximum Ppumpand WHP. The amps should drop as the operating point moves to zero flow.

The blockage in pump stages should show some rise in WHP and Ppumpand a decrease in amps.

In this case the pump head curve is degraded and therefore there will be not be the full increase in PpumpandWHP as expected. The amps should drop as the operating point moves to zero flow.

Case WHP Ppump Amps

Hole in tubingSmall

increaseLittle

changeLittle

change

Blockage at pumpintake

Bigincrease

Bigincrease

Decrease

Blockage in pump

stages

Medium

increase

Medium

increase Decrease

Head

Flowrate

Hole intubing

Blockage at pump intake

Blockagein pump

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Field examples using the Pattern Recognition Analysis check sheet (Table 1)

The field examples of 4 ESP operational cases out of the 12 cases captured in the Pattern Recognition Analysischeck sheet will be used to discuss the methodology of using Pattern Recognition analysis for the ESP diagnosis,as a key enabler in achieving consistency in ESP diagnosis and optimization.

The cases will be discussed by first displaying the plots (Pressure Gradient, Pump Curves & Trends) which willsignify the predicted theory and will be cross checked with the actual measured Trend and Nodal Analysis models.The diagnosis steps used are as follows:

1. Cross check with the Pattern Recognition check list using ESP concepts equations (Table 1).

2. Generate Well Models using Nodal Analysis tool to determine Pressure gradient plots to cross check withthe predicted Pressure Gradient plot

3. Analyze the Pump Curve from Nodal Analysis model to infer the operating point due to the operationalcase compares to the normal operating point (pre-abnormal operation).

4. Where available, the pull report and DIFA report will be shown to confirm the Pattern Case. The othercases from the Checklist will be discussed in the paper Presentation.

Broken shaft Pattern Recogni tion Description (Theory)

Broken Shaft matching Pattern Recognition (Field Example)

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Descrip tion on measured data trend (real time Web Monitor ing Data System) match Broken Shaft cases:

- No change in WHP, discharge or intake pressures on restart (Feb 3)

- Discharge pressure much lower than normal, indicating fluid level below surface (therefore, no flow)

- Zero pump dP (at no flow should be at maximum head, unless zero stages rotating) (trip parameter)

- Sharp spike in current indicates shaft shear on restart, then much lower than normal (trip parameter)

- Gas separator shaft found sheared from bottom and sheared part stuck on coupling (pull report)

Pull Out Report showingthe broken shaft of the gas separator

Hole in the Tubing Pattern Recognition Description (Theory)

Be ore break

Operating point

(after break)

Operating point

(before break)

Broken shaft on restart

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TRENDPLOT

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Hole in the Tubing - recirculation (Field Example)

Descrip tion on measured data trend (real time Web Monitor ing Data System) match Hole in the Tubing

- Slow decline in WHP (commencing around Feb 25) indiciating a drop in flowrate at surface- Slow, small decline in current (corresponds moving along the load curve to the right, i.e. high flowrates)- Slow decline in discharge pressure (exactly matched decline in WHP)- Slow increase in intake pressure (indicating a decline in pump dP or head as flowrate increases)- Delayed but then sharp rise in measured temperatures (lag due to sensor location at motor base)- Final, stabilised pump dP is determined by hole location and size (best trip parameter)

Pump Curve: To continue with the diagnosis, the nodal analysis (on quick look functionality) is used to generatethe operating point on Pump curve as shown below, which indicate that the head has dropped while the Pump flowrate (Q) is on the up thrust position indicating a recirculation case. The slight observed decline in current is mainlydue to the corresponding load curve which is usually lower at very high flowrates..

Blockage at Perforations Pattern Recognition Descrip tion (Theory)

Before circulation

Hole located at joint 79 fromsurface (approx. 270 m

above pump)

Operating point

(normal)

Operating point

(recirculation)

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Blockage at Perforation Real Example

Blockage at Perforations

Descrip tion on measured data trend (real time Web Monitor ing Data System) match Blockage atPerforations

- Multiple pump starts with regular trips on low intake pressure (pump off)

- Slow decline in WHP over 1 day flow period (variations indicates flowline slugging = low flow)

- Slow decline in discharge pressure (mirrors decline in WHP, also slugging in wellbore = low flow)- Variation in current matches slugging cycles (load changes with flowrate)

- Intake pressure continuously declining over flow period

- Decreasing flowrate (from WHP) and decreasing intake pressure indicate a reservoir problem (IPR)

High pump dP with

low intake pressure

Inflow performance

curve

Operating point

(close to pump off)

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Increase in water cut Pattern Recognition Description (Theory)

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Increase in Water Cut Real Example

Descrip tion on measured data trend (real time Web Monito ring Data System) match Increase in WC

- Very gradual decline in WHP indiciating a drop in friction in flowrate at surface (less gas, more water)

- Slow increase in current (load increasing due to pump fluid density increasing)

- Slow increase in discharge pressure (heavier fluid in tubing)

- Slow increase in pump dP (= head * fluid density) as water cut increases

- No change in motor temperature

Working toward ESP Exception Base Surveillance (ESP EBS)Operatingpoint (52%

Operating

point (89%

High WCLow WC

Initial flow up casing

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Since all the ESP wells have down-hole sensors and are on real time monitoring, the Pattern Recognition Analysiscan be grouped monitored as Exception Base Surveillance by introducing Alarms and Trips values.

Setting Alarms and Trips

In order to achieve the ESP EBS, it is essential to determine the right values for Alarms & Trips. In some cases,the values may vary per well as well per field. Using Pattern Recognition check list, it is aimed to apply these

trends into Alarms & Trips setting. In this section, the setting of Alarms & Trips in relation to Pattern Recognitioncheck list will be discussed.

The ongoing attempt on using this Check list to the in-house well web-base system, NIBRAS, will be discussedand the plan to introduce this unique ESP EBS in LOWIS will be discussed. In the mean time, the PatternRecognition Checklist is used on individual case basis while in the future is to integrate in the LOWIS software asadditional functionality on ESP EBS.

There are three key major parameters for setting Alarms and Trips, namely:

1. Amps:

Overload usually set at +15% of running Amps

Under load usually set at 1 15% or 20% of running amps, but could be 40% for gassy wells or pumps with a loadcurve that decreases sharply at low flow rates.

2. Surface and Downhole Pressure

These provide the best protection since they respond immediately to a problem.

Wellhead pressure (high trip) indicates a shut in at surface downstream of the WHP sensor (e.g. choke).

Pump discharge pressure (high trip) indicates a shut in at surface or restriction in the tubing or tree.Pump discharge pressure (low trip) indicates loss of flow and fluid level below surface.

Pump intake pressure (low alarm or trip) indicates loss of inflow (pump off).

Ppump(high alarm or trip) indicates operation in down thrust (zero or low flow).

Ppump(low alarm or trip) indicates operation in up thrust (high flow, usually recirculation).

All of these parameters can be calculated using the equations given on page 2 or from software such as Prosper or

SubPump or Autograph. Ppumpgives the best indication of pump operating condition.

Note that the Ppumpsettings are dependent on density and frequency so must be recalculated accordingly.

3. Motor Temperature (high trip)

This is a lagging indicator, since the greatest source of heat is usually the pump which is a long way from thesensor (located at the motor base). It is usually set at 125 C, but better to be customized to the well conditions bysetting at normal running temperature plus, for example, 15 C.

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Testing ESP EBS using Pattern Recognition Analysis in NIBRAS

Two cases were tested to establish ESP EBS in NIBRAS

Alarm Defini tion

Alarm

Name

Current Motor Temp THP Discharge

Pressure

Intake Pressure

Hole inTubing

Same or slightdecline OR

Slowly increase

Slowly increase-5% of set

Decline by 5%-5% of set

Slowly increase

Shut in atSurface

Decline-15% of set

Slowly increase

Increase by 10%+10% of set

Increase by 10%+10% of set

Increase

Table 2 Alarm setting in Nibras ESP EBS

NIBRAS test server was created and Alarms value / range were put forward followed by Pattern Recognitionchecklist for ESP EBS. It is expected that some of the values might need revision as the rate of change of somevariables, such as Temp / Amps might vary from well to well and from field to field.

It has been realized that there are some Pattern Recognition cases with similar Alarm values such as Hole in theTubing and the Blockage at Pump Intake would be difficult to achieve ESP EBS by only using Pattern Recognitiontrending. The ESP EBS needs to include the Well Model to show the Pump Curve where the Amps are slightlydecreased due to the power load current at high flow rate. Hence, this demonstrates the limitation of Trending toolswithout proper nodal analysis software.

Way forward

Testing ESP EBS using Pattern Recognition Analysis in - LOWIS.

It is important that well surveillance integrated systems have the capability of well modeling to proper use thePattern Recognition Check list in ESP diagnosis in the report such as ESP EBS. Hence tool such as LOWIS is keyin using Pattern Recognition in ESP diagnosis because of its ability of performing Well Models (Nodal Analysis),which a basic limitation element for the in-house web base report portal systems - NIBRAS.Currently, PDO is integrating pattern recognition analysis into Nodal Analysis tool. All identified cases will beprobably implemented to Nodal analysis to reflect the benefit of this level of advance diagnoses.Eventually, Pattern Recognition will be fully automated in real time, web base Nodal Analysis tool to enable theanalysis & diagnoses of huge data in a particular field.

Challenges:

To be able to achieve full integration of pattern recognition into real time, web base Nodal Analysis software.Keeping all the models are up to date with most recent well test & subsurface data. It is important that alltransmitted data are accurate and maintain. In addition, Human inter-action is critical to ensure corrective actionsare taking on bored.

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Conclusions:

A Pattern Recognition analysis check sheet is being used in ESP diagnosis which enables a quick and consistencyinterpretation across PDO in those identified 12 cases. Few cases were demonstrated in PDO by matching thePattern Recognition analysis tool with pulled out ESP reports.

Few of the Pattern Recognition cases which have similar response trends needs a further field test to confirm the

case; for example between Hole in Tubing; Blockage at pump intake and Blockage in pump stages.

ESP well and reservoir performance can be precisely predicted from simple physical relationships by matching withthe real time trends of surface and downhole data.

Establishing the Pattern recognition of the trended real time data is a key to make the software intelligent enoughto be effective to the work places.

As a way forward in ESP monitoring, the work is ongoing in establishing the ESP EBS using Pattern Recognition inthe integrated web-base Nodal Analysis software (LOWIS) by combining real time with the well models by buildingcorresponding logics.

Applying Pattern recognition principle can significantly increase in ESP up time / run life will be achieved.

Appendix 1: Trip Parameters & Values

Currenta. Current Overload Trip - Overload setting is used to trip the ESP motor when motor current exceeds this value

thereby preventing the motor from getting damaged.We set overload at 115 % of motor nameplate amps. For example if motor nameplate amps is 40 A, overloadsetting will be 40 * 1.15 = 46 A.

b. Current Underload Trip -- Underload setting is used to trip the ESP motor when motor current drops below thisvalue thereby preventing the motor from getting damaged.We set underload at 80 % of motor running amps. For example if motor nameplate amps is 40 A, and motorrunning amps is 35 A, then underload setting will be 35 * 0.8 = 28 A.

c. Current Unbalance Trip -- Current unbalance trip setting is used to trip the ESP motor when unbalance in thethree phase currents of motor exceeds this value.We set current unbalance trip setting at 20 % or 25 %. So if the unbalance between the three phase currents ofthe motor exceeds 20 % or 25 %, it will trip the ESP motor.

Voltaged. Overvoltage Trip -- Overvoltage trip setting is used to trip the ESP motor when incoming voltage to the motor

exceeds this value.We set overvoltage trip at 110 % of required motor voltage. For example if required motor voltage is 1700 V, thenovervoltage trip setting will be 1700 * 1.1 = 1870 V.

e. Undervoltage Trip -- Undervoltage trip setting is used to trip the ESP motor when incoming voltage to the motordrops below this value.We set undervoltage trip at 90 % of required motor voltage. For example if required motor voltage is 1700 V,then undervoltage trip setting will be 1700 * 0.9 = 1530 V.

f. Voltage Unbalance Trip -- Voltage unbalance trip setting is used to trip the ESP motor when unbalance in thethree phase voltages of motor exceeds this value.We set voltage unbalance trip setting at 6 % or 8 %. So if the unbalance between the three phase voltages of themotor exceeds 6 % or 8 %, it will trip the ESP motor.

Surface Pressureg. High Tubing Head Pressure -- This setting is done in the pressure switch which is installed in the tubing line of

wellhead. The pressure switch will trip the ESP motor when tubing pressure exceeds the setting value. Generallyhigh tubing pressure trip setting is 35 or 50 bar (In Yibal / Alhuwaisa field).

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h. High Flowline Pressure -- This setting is done in the pressure switch which is installed in the flowline. Thepressure switch will trip the ESP motor when flowline pressure exceeds the setting value.Generally high flowline pressure trip setting is 14 or 26 bar (In Yibal / Alhuwaisa field) depending on GRE orcarbon steel flowline.

Subsurface Pressure/Temperaturea. Low Pump Intake Pressure -- Low PIP trip setting is used to trip the ESP motor when pump intake pressure

drops below the setting value. This setting is different for different wells depending on the PIP of each particularwell.

b. Pump Motor Temperature Trip -- Motor temperature trip setting is used to trip the ESP motor when motortemperature rises above this setting value. Generally we set the motor temperature trip at 125 or 130 degreeCelsius.

Nomenclature

ESP Electrical Submersible Pump EBS Exception base surveillance

Pi Pump Intake Pressure AL Artificial Lift

Pd Pump Discharge Pressure PDO Petroleum Development Oman

Tm Motor Temperature MOG Ministry of Oil & Gas

Tpi Pump Intake Temperature ESP-SME ESP-Subject Matter ExpertAPI American Petroleum Industry VU Voltage Under load

BSW Base Sediments & Water CU Current Under load

THP Tubing Head Pressure SCADA Surveillance Computer Assisted Data Acquisition

TVD True Vertical Depth

Figures and tables

Figure 1 Real time flow chart

Figure 2 Cable failureFigure 3 Impeller Scale depositionFigure 4 Repetitive tubing leak plotFigure 5 Repetitive mechanical failuresFigure 6 Pull out broken shaft pictureFigure 7 Pull out hole in tubing picture

Table 1 Patterns Recognition Analysis checklist

Table 2 Alarm setting in Nibras ESP EBS

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References

1. Electrical Submersible Pumping System: Striving for Sustainable Run-Life Improvement in Oman oil; by AtikaAl-Bimani & Samuel Armacanqui; Buthaina Al-Barwani; Iqbal Sipra; Said Al-Hajri & Halima Al-Riyami; IPTC 12601; 2008 Kuala Lumpur Malaysia

2. Focus ESP Surveillance in Sensitive Conditions: Benefits & Challenges by Ibrahim Al-Siyabi, Hamed Al-Sharji, Atika Al-Bimani; - PDO: 24

thAnnual ESP Workshop in Gulf Coast Houston April-2007

3. PDO Level 1 Training Course; ESP Systems Design, Diagnosis and Optimization Engineering InsightsLimited, 2011/2012

4. PDO Level 2 Training Course; Advanced ESP Systems Modeling & Analysis Workshop using Prosper &Shurooq Engineering Insights Limited, 2011/2012

Acknowledgements

The authors acknowledge the support of the Ministry of Oil and Gas, Oman (MOG), and the management ofPetroleum Development Oman for providing the environment to do this work and granting permission for this paperto be published. In addition, the authors acknowledge the North & South Directorates, Petroleum EngineeringDirectorates & supporting directorates (Well Engineering, & Automation) for their endless contribution in making

the companys ESP management and operation a success.