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1 THE WIRELESS DOWNHOLE PRODUCTION PROFILE Discover more • www.resman-themovie.com

Rigless Production Monitoring- Chemical Production Logging Technology

Dr. Christian A. Andresen Sr. Tracer Surveillance Analyst

[email protected]

mailto:[email protected]

2 THE WIRELESS DOWNHOLE PRODUCTION PROFILE

Outline

• Technology fundamentals – How It Works

• Case Study

• Flow loop verification

• Q&A


Riskfree Downhole Surveillance


Molecule Release Constant release rate

(Flow rate independent)

TRACER SYSTEM Up to 90 (50 oil + 40 water)

unique intelligent molecule IDs

Unique tracer molecule

Polymer Matrix

Integration to well completion

How it Works • Fundamentals

CARRIER ASSEMBLY Pup-joint or standard completion component

FLUID CONTACT Triggers oil or water tracer release


How it Works • Sampling and Interpretation

Sample Production

Lab Analysis

Downhole Surveillance Information

Data Interpretation In house team of analysts


How it Works • Integrating Tracers in Completion

Integration of RESMAN tracer rods into screens

Integration of RESMAN tracer filaments into premium mesh screens

RESMAN rods and filaments

integrated with carrier

Identification for well completion


What can tracer technology provide ? Permanent Production Surveillance

• Inflow distribution

• Water influx detection

• Inflow assurance • Are all zones contributing ? • Are mechanical devices working ? • Are all wells/zones/laterals flowing ?

?


ICD case study

5 1/2’’ Weatherford MaxFlo ICD screen

• Sub-sea development

• 19 km tie-back to platform

• Dual lateral ICD completed well

• 10 oil and 10 water tracer systems installed


• Sample selection done by PVT analysis, compared to OLGA simulation

ICD case study – sampling and production data


ICD case study – re-start tracer responses A) Steady-state released tracer from last production period

B) High concentration fluids from shut-in period

C) Steady-state response from stable production

All tracers detected and within expected levels: Production at toe of

both laterals confirmed, flow past all tracers confirmed

A

B

C


Flush-out theory

• Shut-in fluids assumed stagnant

high concentration volumes form

• Once the well is started up

high tracer concentration cloud will be flushed-out

• The rate of decline in the tracer concentration is dependent on

the production past the tracer carriers

• Flow estimations are based on history-matching. A steeper

curve signifies a higher flow past the tracer systems and thus

higher production Q in the section

Q

2Q


Tracer systems placed inside the ICD screen


Systems come in contact with oil they release a unique chemical fingerprint (tracer) into the oil


When well is in a static condition, the concentration of tracer builds up around the vicinity of screen


During initial production, flow from reservoir flushes out the oil with the high concentration


Inflow rate from the reservoir determines how fast the ICD is flushed out


Oil with high concentration of tracer enters the main flow path and is carried to surface


Eventually a steady state concentration occurs which is the result of the total flow rate and the tracer release rate

Q

2Q


Flow loop testing – Project configuration

Work awarded to IFE • 30+ years R&D activity in multi-

phase flow (inventor of OLGA) Full scale experiment • Up to 2000 m3/day base pipe loop-

flow and 100 m3/day annular flow • Annular pressure chamber 12’’x12m • Real-time parameter measurements


Flow loop testing – experimental lay-out

Annular reservoir

Main reservoir 15 m3

F

F

F F F

F Flourometer

Flowmeter


Flow loop testing – experimental lay-out

Current configuration • 6 5/8” HALLIBURTON ww sandscreen testing • Basepipe flow: 100 – 2000 m3/day variations • Annular flow: 3 - 72 m3/day variations • Multiple inflow variations tested for model verifications


Flow loop testing – Results changing annular flow rate


Flow loop testing – Model fit vs. experimental values

Experimental flow rate

RE

SM

AN

mo

de

l e

sti

ma

te

RESMAN quantitative flow models are well suited for flowback interpretation


RESMAN flush-out model shows

excellent fit to experimental data

Model incorporated into iRES

Flow loop testing – results


Tracer Flush-out Curve Fittings

k9 = 1.00 k7 = 0.41

k10 = 0.45 k8 = 0.52

k4 = 0.38

k2 =

0.41

k5 = 0.59

k3 = 0.45 k6 = 0.52

k1 =

0.45

• Flush-out response fitted for cumulative produciton > 1000 m3


Tracer Flush-out Production Estimates

• Production from both monitred and non-

monitored zones included


Thank you for your time

www.resman.no and www.resman-themovie.com

http://www.resman.no/

http://www.resman-themovie.com/



rigless production monitoring- - spe-uk.org · pdf filerigless production monitoring- ......

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