Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery DAVIS Department of Petroleum Engineering Texas A&M University College.

Slides:



Advertisements
Similar presentations
Forecasting Models With Linear Trend. Linear Trend Model If a modeled is hypothesized that has only linear trend and random effects, it will be of the.
Advertisements

Analytical Solutions for a Composite, Cylindrical Reservoir with a Power-Law Permeability Distribution in the Inner Cylinder Ryan Sawyer Broussard Department.
Slide Sets to accompany Blank & Tarquin, Engineering Economy, 6 th Edition, 2005 © 2005 by McGraw-Hill, New York, N.Y All Rights Reserved 18-1 Developed.
Harold Vance Department of Petroleum Engineering
Chih-Yuan Chang, Eric Faust, Xiangting Hou, Dr. Kuo-Jen Liao Department of Environmental Engineering October 28, 2014 Investigating Ambient Ozone Formation.
Reservoir Engineering Aspects of Unconventional Reservoirs
Well Testing — Historical Perspectives
Contemporry Engineering Economics, 4 th edition, © 2007 Equivalence Calculations with Continuous Payments Lecture No.12 Chapter 4 Contemporary Engineering.
Decline Curve Analysis Using Type Curves —
Contemporary Engineering Economics, 4 th edition, © 2007 Unconventional Equivalence Calculations Lecture No. 9 Chapter 3 Contemporary Engineering Economics.
Analysis of Production Data
Analysis of Layered Gas Reservoir Performance Using a Quasi-Analytical Solution for Rate and Pressure Behavior I Nengah Suabdi Department of Petroleum.
Oil Field Manager ~ Presentation
Calibration & Curve Fitting
Thesis Defense College Station, TX (USA) — 05 September 2013 Landon RISER Department of Petroleum Engineering Texas A&M University College Station, TX.
Principal Investigators: Ding Zhu and A. D. Hill
SPE Distinguished Lecturer Program The SPE Distinguished Lecturer Program is funded principally through a grant from the SPE Foundation. The society gratefully.
Semi-Analytical Rate Relations for Oil and Gas Flow
Schlumberger Public Scope and Application of Pressure Transient Tests in CBM and Shale Gas reservoirs Baijayanta Ghosh Reservoir Domain Champion Testing.
EVENT MANAGEMENT IN MULTIVARIATE STREAMING SENSOR DATA National and Kapodistrian University of Athens.
Kansas Geological Survey State Energy Resources Coordination Council
Calgary Petroleum Club – February 19, 2013 “Production Performance Unique Type Curve for Horizontal, Multi-Stage Frac'd Gas Wells: WHY, HOW and WHEN!”
University of Southern California Background Photo by NASA, date unknown Texas A&M University Big GeoData Problems – High Volume Transactions and National.
Slide Sets to accompany Blank & Tarquin, Engineering Economy, 6 th Edition, 2005 © 2005 by McGraw-Hill, New York, N.Y All Rights Reserved 2-1 Developed.
Slide Sets to accompany Blank & Tarquin, Engineering Economy, 6 th Edition, 2005 © 2005 by McGraw-Hill, New York, N.Y All Rights Reserved 12-1 Developed.
DEPARTMENT OF STATISTICS  What are they?  When should I use them?  How do Excel and GCs handle them?  Why should I be careful with the Nulake text?
Production Analysis of Western Canadian Unconventional Light Oil Plays (SPE ) C.R. Clarkson and P.K. Pedersen T O C © TOC, 2011.
Integration of Production Analysis and Rate-Time Analysis via Parametric Correlations — Montney Shale Case Histories Yohanes ASKABE Department of Petroleum.
Michael Fay VP, Software Development. Well Production Forecasting Requirements For efficiency, the method should be simple (e.g. no simulation or complex.
Boyd Russell A Practical Guide to Unconventional Petroleum Evaluation Petroleum Club November 28, 2012 R eservoir E valuation P roduction O ptimization.
2 Methodology Overview Generation of Correlated Ensemble Scenarios ② Cholesky decomposition ③ Correlated ensemble matrix, Y ④ Generating observation according.
Slide Sets to accompany Blank & Tarquin, Engineering Economy, 6 th Edition, 2005 © 2005 by McGraw-Hill, New York, N.Y All Rights Reserved 11-1 Developed.
JAMES KAIHATU, JOHN GOERTZ, YING-PO LIAO, RICHARD IRWIN AND DEIRDRE DEVERY COASTAL AND OCEAN ENGINEERING DIVISION ZACHRY DEPARTMENT OF CIVIL ENGINEERING.
Final Presentation College Station, TX (USA) — 11 August 2015 Chulhwan SONG Department of Petroleum Engineering Texas A&M University College Station, TX.
Eagle Ford Shale Study November 11, Overview Map Eagle Ford Shale Study – Area Overview.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 3 Describing Relationships 3.2 Least-Squares.
Capillary Pressure Brooks and Corey Type Curve
Nugget: Determining Optimal Sensor Locations for State and Parameter Estimation Juergen Hahn Artie McFerrin Department of Chemical Engineering Texas A&M.
Local Predictability of the Performance of an Ensemble Forecast System Liz Satterfield and Istvan Szunyogh Texas A&M University, College Station, TX Third.
A Semianalytical p/z Technique Abnormally Pressured Gas Reservoirs
Daniel J. Cruz Dept. of Physics and Astronomy Texas A&M University.
Slide Sets to accompany Blank & Tarquin, Engineering Economy, 6 th Edition, 2005 © 2005 by McGraw-Hill, New York, N.Y All Rights Reserved 6-1 Developed.
Selecting Appropriate Projections Input and Output Evaluation.
Irwin/McGraw-Hill © Andrew F. Siegel, 1997 and l Chapter 14 l Time Series: Understanding Changes over Time.
Abnormally Pressured Gas Reservoirs
27 May, 2011 — College Station, TX Study of Nonideal and Secondary Fractures O.M. Olorode Slide — 1/18 A Numerical Study of Nonideal and Secondary Fractures.
1 12. WORLD ELECTRICITY IN THE YEAR 2050 Asko Vuorinen.
Diffusivity Equations for Flow in Porous Media PETE 613 (2005A) Slide — 1 T.A. Blasingame, Texas A&M U. Department of Petroleum Engineering Texas A&M University.
Yohanes ASKABE Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Slide — 1/80 Rate-Decline.
Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Antu Xie Modelling Concepts for Fracture.
STATISTICS 13.0 Linear Time Series Trend “Time Series ”- Time Series Forecasting Method.
Forecasting. Model with indicator variables The choice of a forecasting technique depends on the components identified in the time series. The techniques.
Final Presentation College Station, TX (USA) — 11 August 2015 Chulhwan SONG Department of Petroleum Engineering Texas A&M University College Station, TX.
Class # 7 Slide Sets to accompany Blank & Tarquin, Engineering Economy, 6 th Edition, 2005 © 2005 by McGraw-Hill, New York, N.Y All Rights Reserved 5-1.
Yandell – Econ 216 Chap 16-1 Chapter 16 Time-Series Forecasting.
Lecture 9 Forecasting. Introduction to Forecasting * * * * * * * * o o o o o o o o Model 1Model 2 Which model performs better? There are many forecasting.
Chapter 5 Well Testing (III)
Equivalence Calculations with Continuous Payments
Equivalence Calculations with Continuous Payments
Chapter 5 Pressure Transient Testing (I)
Brooks-Corey MICP Model Parameters Determination
Petroleum Engineering 631 — Petroleum Reservoir Description
SPE DISTINGUISHED LECTURER SERIES
Decline Curve Analysis Using Type Curves —
MS Thesis Defense — Fall 2016
Masters of Science Thesis Defense
Texas A&M Industrial Engineering
Formalized Sensitivity Analysis and Expected Value Decisions
Lesson #2: The Rate of Change
Reservoir Engineering Aspects and Forecasting
Presentation transcript:

Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 1/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 2/35 Project Overview: ● Production Analysis Workflow  Data Correlation Verification  Preliminary Time-Rate Diagnostics  Time-Rate Relation Models ● 30-Year Cumulative Production Forecast ● Summary & Conclusions ● Ongoing & Future Work Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Production Analysis Workflow Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 3/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 4/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015) Model Based Analysis Exponential & Hyperbolic Relations Semi-Analytical Rate-Cumulative Techniques Flowing Material Balance Preliminary Time-Rate Diagnostics Review & Edit Production DataIdentify Flow Regime(s) Data Correlation Verification Required Data Production DataWell HistoryReservoir and PVT Data Source: Ilk [2010]

Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Production Data & Data Correlation Verification Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 5/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 6/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 7/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015) Well Cleanup Effects? Transient Responses Inaccurate Data Acquisition?

Slide — 8/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 9/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015) Well Cleanup Effects? Transient Responses Inaccurate Data Acquisition?

Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Editing Production Data Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 10/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 11/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 12/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 13/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 14/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Preliminary Time-Rate Diagnostics Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 15/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 16/35 1:4 Slope (low F cD ) 1:2 Slope (high F cD ) 1:1 Slope Depletion Compound Linear Flow Regime Formation Linear Flow Regime Bilinear Flow Regime Elliptical Flow Regime Production Time Production Rate Transition Regime Time-Rate: Multi-Fracture Horizontal Well Flow Regimes Source: Blasingame [2011] Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 17/35 Diagnostic Time-Rate Functions: Source(s):- Arps [1945, 1956] - Ilk et al. [2008] Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 18/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015) Identify Flow Regime(s): 1:2 Slope (Linear) 1:1 Slope (Depletion)

Slide — 19/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015) Identify Flow Regime(s): 1:2 Slope (Linear)

Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Model Based Exponential & Hyperbolic Time-Rate Relations Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 20/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 21/35 Modified Hyperbolic Decline: Source(s):- Arps [1945, 1956] - Robertson [1988] Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 22/35 Stretched Exponential Decline: Source: Valk ό. [2009] Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 23/35 Power-Law Exponential Decline: Source: Ilk et al. [2008] Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 24/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 25/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 26/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 27/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 28/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 29/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations 30-Year Cumulative Production Forecast Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 30/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Modified Hyperbolic (BSCF) Power-Law Exponential (BSCF) Stretched Exponential (BSCF) Slide — 31/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Modified Hyperbolic (BSCF) Power-Law Exponential (BSCF) Stretched Exponential (BSCF) Slide — 32/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Summary & Conclusions Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 33/35 Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Slide — 34/35 ● Rate-Time Analysis Workflow  Edit production data to remove production noise and irregularities.  Calculate the diagnostic D(t), b(t), and β(t) functions.  Select the appropriate decline curve models based on the general trends of the data diagnostic functions.  Generate decline curve model solutions for q(t), D(t), b(t), and β(t) functions.  Plot [log-log] the well’s production and diagnostic functions along with the model solutions for visual inspection. ● Decline Curve Models  Understand the well’s flow regimes. What is the current flow regime? When will BDF occur?  Realize the assumptions inherent to the models.  Sensitive to noise and irregularities in production data.  Large variability in the 30-year EUR estimate between models. Modified Hyperbolic is typically the highest EUR estimate. Power-Law Exponential is typically the lowest EUR estimate. Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015)

Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Production Analysis of Eagle Ford Shale Gas Wells using Time-Rate Relations Avery Davis — Texas A&M University (8 February 2015) Evaluation & Workflow of Eagle Ford Shale Gas Wells using Time-Rate Relations End of Presentation Avery DAVIS Department of Petroleum Engineering Texas A&M University College Station, TX (USA) Presentation for Directed Studies (PETE 685) College Station, TX (USA) — 8 February 2015 Slide — 35/35