integration of petroleum and reservoir engineering

Integration of Petroleum and

Reservoir Engineering Workflows

into a Production Database

Management System to Increase

Operational Efficiency

Asset Optimization- Improving Production Rates,

Operational Efficiency & Reservoir Recovery

29th October 2015

Andrew Hyde

DEA Deutsche Erdoel AG PAGE 2Asset Optimization- Improving Production Rates, Operational Efficiency & Reservoir Recovery

Asset Overview – Breagh

• Located in the SNS

• 8/10 wells drilled from Alpha

platform

• 120km Pipeline back to Teesside

Gas Processing Plant

• Up to 9 additional wells to drill in

Phase II Development

• 60o wells

• Enhance well PI

• Multiple producing zones

• Wireline access

• 2 fracced Wells, future wells to be

fracced and some existing wells to

be reentered and fracced

DEA Deutsche Erdoel AG PAGE 3

Current Challenges

› Volume of data overwhelming (P, T, Q, composition, PCS)

› Data reliability (spreadsheets, changing staff, corporate memory, audit trail)

› Data integrity – data can get corrupted in spreadsheets/have bugs, managing

access to the data

› Data accessibility (recording changes, access across departments)

› Consistent models (Eclipse, Petrel, GAP, Prosper, Consistent paramaters)

› Efficiency (Saving engineers time to focus on engineering)

Asset Optimization- Improving Production Rates, Operational Efficiency & Reservoir Recovery


Objective

› Implementation of a Production Data Management System (PDMS),

Manageable

Reliable

Accessibility

Data integrity – data can get corrupted in spreadsheets, managing access

to the data

› Workflows

Standardise

Automate

Integration of multiple work flows and software

Operational Efficiency (Saving engineers time to focus on engineering)

› Reporting


Increase Operational Efficiency


PDMS - Overview


Spreadsheets

(Internal and 3rd party)

Data historian

(PI/Honeywell)

Models

Avocet

Workflows

Schematics/

Reports

Reports

Forecasts

KPIs

Facilitating active

management and

informed decision

making

QC

Processes


PDMS - Content

› Have direct link to data Honeywell data historian

› Automated input of 3rd party spreadsheets

› Basic QC processes Actual and Allocated Wobbe Index compared, 3rd

party data

› Key document database

Compositional gas analysis

Water analysis

Completion diagrams

› Audit trail for every input



PDMS – Access and Visualisation


Visualisation of Data

Automatic loading of data

Quick access to historic data


Workflows - Overview



Workflows - Allocation Automation


› Basic calculation and conversions

Audit of factors used

› Production Allocation

Multiple methodologies used to confirm allocation

Time consuming

Multiple tools used (spreadsheets, hydraulic modelling & PTA software)

› Three key processes to automate

Rate values from IPR curve

Daily productivity index (PI) calculation

Rate values from wellhead temperature curve


Workflows – Rate from IPR Curves

› Based on initial productivity

› Benchmarked by PBU analysis (changing pressure and skin)

› Interpolation between latest data points

› Main allocation technique



Workflows – Productivity Index Calc.

› Productivity Index calculated on a

daily basis, based on a calculated

linear decline of pressure between

two PBU’s

› Changes in PI indicate either:

› Incorrect Allocation

› Changing wellbore conditions


𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑖𝑡𝑦 𝐼𝑛𝑑𝑒𝑥 =𝐹𝑙𝑜𝑤𝑟𝑎𝑡𝑒

(𝑅𝑒𝑠𝑒𝑟𝑣𝑜𝑖𝑟 𝑃𝑟𝑒𝑠𝑠𝑢𝑟𝑒2 − 𝐵𝑜𝑡𝑡𝑜𝑚 𝐻𝑜𝑙𝑒 𝑃𝑟𝑒𝑠𝑠𝑢𝑟𝑒2)


Workflows – Wellhead Temp. Correlation

› Rate based allocation based on Wellhead Temperature correlation

› Previous 6 months allocated rate data plotted against wellhead temperature

› Largest error bar associated with this methodology


0

2

4

6

8

10

12

14

16

30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120 125 130 135 140

Gas

Rat

e -

MM

scfd

THT- ºF

Rate-Temperature Correlation

A5z


Workflows – Integration with other

software

› Data automatically fed into third party software:

Well Test Analysis

Rate Transient Analysis

Decline Curve Analysis

Reservoir Simulation


1.00

10.00

100.00

0.00 10,000.00 20,000.00 30,000.00 40,000.00 50,000.00 60,000.00 70,000.00 80,000.00 90,000.00 100,000.00

Rat

e (

mm

scfd

)

Cum Gas (mmscf)

Breagh 42/13a-A8

10-2 10-1 100 101

10

-410

-310

-2

Delta-T (hr)

DP

& D

ER

IVA

TIV

E (

MP

SI2

/CP

/MS

CF

/D)

STABIL

13-SEP-2014 23:1520-SEP-2014 11:1821-SEP-2014 20:40

2014/09/21-2040 : GAS (PSEUDO-PRESSURE)

Skin(darcy) = -2.0295

permeability = 6.5000 MD

Perm-Thickness = 403.00 MD-FEET

Turbulence = 0. 1/MSCF/D

P-extrap. = 3405.73 PSI

R(inv) at 0.6358 hr = 102. FEET

Smoothing Coef = 0.,0.

Static-Data and Constants

Volume-Factor = 1.080 RB/MSCF

Thickness = 62.00 FEET

Viscosity = 0.01980 CP

Total Compress = 0.0001477 1/PSI

Rate = 12000. MSCF/D

Storivity = 0.001282 FEET/PSI

Diffusivity = 4187. FEET^2/HR

Gauge Depth = N/A FEET

Perf. Depth = N/A FEET

Datum Depth = N/A FEET

Analysis-Data ID: OPC01

Based on Gauge ID: OPC01

PFA Starts: 2014-09-06 05:30:00

PFA Ends : 2014-09-22 06:25:00


Reporting - Overview

› Single auditable source of data for

Management reporting

Regulator

Partners

› Standardised reporting

› On demand access to data

› Live data to feed dashboard KPI



Summary – We have:

› Implanted a robust, auditable database

Improved the management and quality of our data

One version of truth across the business

KPIs visible and accessible to management

› Increased Operational Efficiency through time saving and increased focus on

value adding activities

Automation of some work flows (and striving to automate more)

Controlled transfer of data between applications

Management by exception

› Improved data accuracy and reliability without additional work load through

work flow automation.

› Already kicked off project to implement Avocet across all out operated and non

operated sites


Thank You

Questions?

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