V.C. KELESSIDIS Technical University of Crete Mineral Resources Engineering AMIREG 2009 Athens, September 7-9, 2009

Transcription

1 NEED FOR BETTER KNOWLEDGE OF IN-SITU UNCONFINED COMPRESSIVE STRENGTH OF ROCK (UCS) TO IMPROVE ROCK DRILLABILITY PREDICTION V.C. KELESSIDIS Technical University of Crete Mineral Resources Engineering AMIREG 2009 Athens, September 7-9, 2009

2 Research aim Optimization of drilling rates Less expensive and safer drilling practices Hydrocarbon, geothermal, mining, water well drilling Multitude of parameters affecting drilling performance Rock Strength Availability of data and proper modeling software Optimum combination better drilling rates 2

3 The problem Drilling allows for access to subsurface target areas Pythagoras saying whoever digs, finds, he who never digs, will never find Drilling is expensive Optimum drilling practice arrive to target in the most economical way, but with safety Main monitoring parameter Penetration Rate (m/h) Depends on two main groups Formation Drilling parameters 3

4 Main parameters FORMATION Local stresses Rock compaction Mineralogical content Fluid pore pressure DRILLING Weight on bit and torque Rpm Hydraulic parameters Bit condition 4

5 Modeling drilling process Teale (1965) Rock-bit interaction Energy to the bit Efficiency of energy transfer ENERGY PER UNIT VOLUME SE WOB t = + Abit ( RPM)( D)( WOB / A ) 8 µ ROP bit ROCK-BIT MODEL ROP = UCS = eff SEt ( 8 )( RPM )( µ D)( WOB / Abit) UCS eff WOB Abit 5

6 Laboratory UCS - measurements standard procedures (ISRM 1978, ASTM 1984) expensive & time consuming need core Our analysis, petroleum & mining Reported data Extremely large variability & for different rocks Does the name of the rock IMPLY rock strength? 6

7 Rock classification, Tanaino (2005) Data set of 1000 rock samples 7

8 Rock Strength Factors affecting it Weathering how to account for this? Weak and Strong rock definitions? FACTORS INFLUENCING poor cementation weathering tectonic disturbance porosity mineral composition particle size MAIN ISSUE GET FAIR ESTIMATE OF UCS 8

9 How about CCS? 9

10 Indirect UCS estimation Measurements time consuming & expensive Require core data VARIETY OF ESTIMATION METHODS From cuttings, fair successes, LAG TIME! Schmidt hammer test Point load test Impact strength test Less expensive than UCS measurment Require sample Still time consuming Multitude studies, R 2 ~ 0.40 to

11 Estimation of UCS from sonic data Non destructive Sonic velocity - APPLIED ONSITE! Use of ultrasonic pulses Speed of sound depends on rock density, stiffness, mineralogy grain size weathering stress levels water absorption, water content temperature 11

12 Khaksar et al., SPE research, Oil Well drilling derive Apparent Strength from porosity logs Aim, Use the logs to estimate UCS for improving drilling parameter values, wellbore stability, sanding 26 correlations for sandstones 11 correlations for shales 7 correlations for carbonates Poor estimates, can be improved with data an better analysis techniques (fuzzy logic, pattern recognition) 12

13 UCS from sonic data Equations of the form UCS = a b V p A _ UCS = K 1 ( ) K 40 2 t c UCS UCS = p V / V p 1987 = 143,000 e Mc Nally 13

14 Data versus correlations! Oyler et al., 2008 USA data UCS versus Sonic Travel Time Andrew et al., 2007 Data from 10 wells Apparent Rock Strength from log data 14

15 Predictions, Simple versus Complex Zhou et al., 2005 Use of all available geophysical log data 3 wells 2 techniques for data processing Plus McNally Equation R 2 ~ 0.62 to 0.75 Poor prediction! Data, site specific! MEASURE & CALIBRATE 15

16 UCS Vp - Data analysis Various sources, 187 data sets, different rocks Variations > +/- 100%! UCS (MPa) S-Papanacli M-Papanacli C-Papanacli Sharma & Singh Kahraman Vogiatzi McNally L-S1, Moradian & Behnia L-S2, Moradian & Behnia L-S3, Moradian & Behnia L-S4, Moradian & Behnia Sonic velocity (m/s) 16

17 What is the impact of UCS errors? With use of fairly accurate oil-well drilling simulator Uses UCS as main input parameter Can be tuned with real drilling data Once tuned evaluate different scenarios E.g. effect of a higher UCS than the one used Tested on several wells - Example case here Shale, soft sand, hard sand SCENARIO: Increase of UCS by 50% (+/-100%) 17

18 Increase in UCS by 50% UCS+50% UCS Increase may range between 58 and 96%, giving an overall increase in total drilling time for the sections chosen for the simulation of 82% 18

19 Conclusions Need good drilling rate models Related to rock drillability (RD) In their absence, RD ~ UCS There are standard procedures for UCS measurements Time consuming, expensive, need cores Indirect methods exist 19

20 Conclusions In situ estimation sonic velocity measurement Multitude of correlations, UCS Vp Correlation coefficients LOW!, 0.50 to 0.70 Inaccuracies in UCS estimation impacts strongly rock drillability prediction Example case: Increase (error) of UCS by 50% decrease in ROP by 82% 20

21 Conclusions NEED methodologies for Better UCS estimates ROCK BIT INTERACTION They will help greatly drilling industry 21