REDESIGNING COALBED METHANE RESERVOIR ENGINEERING: a reflective analysis

Transcription

1 REDESIGNING COALBED METHANE RESERVOIR ENGINEERING: a reflective analysis Turgay Ertekin Penn State University Fall 2014 Energy Exchange Seminar Series January 22, 2014

2 A MULTIPLE CHOICE QUESTION: REVISITING THE RESERVOIR ENGINEERING SCHOOL FOR COALDBED METHANE PRODUCTION IS NECESSARY, BECAUSE: AS AN ACADEMICIAN, I NEED TO CONDUCT ACADEMIC EXERCISES EXISTING PUBLISH OR PERISH SYNDROME IN ACADEMIA DEMANDS IT OTHERWISE, I WOULD NOT BE ABLE TO MAKE THIS PRESENTATION MY FATHER OWNS COAL PROPERTIES AND WOULD LIKE TO MAXIMIZE HIS PROFIT NONE OF THE ABOVE

3 SOME ALTERNATIVE ANSWERS... * P * P * P * P * P THE PHYSICS OF FLOW IN A COALBED METHANE RESERVOIR DIFFERS FROM ITS CONVENTIONAL PARTS PRODUCING COALBED METHANE AHEAD OF MINING DECREASES METHANE EMISSIONS TO ATMOSPHERE PRODUCING COALBED METHANE CONTRIBUTES TO NATION S ENERGY BUDGET SIGNIFICANTLY PRODUCING COALBED METHANE AHEAD OF MINING OF COAL INCREASES MINE SAFETY AND MINING EFFICIENCY UNMINEABLE COALSEAMS CAN PROVIDE POTENTIAL CO 2 SEQUESTRATION SITES

4 ACKNOWLEDGEMENTS TRW U.S.STEEL AMOCO GRI DOE/NETL MERIDIAN OIL

5 DIVERSITY IN COALBED METHANE TECHNOLOGY ALONG WITH RESERVOIR ENGINEERING, COALBED METHANE PRODUCTION PRESENTS A SPECIAL CHALLENGE TO: EXPLORATION GEOLOGISTS DRILLING AND COMPLETION ENGINEERS LOG ANALYSTS STIMULATION ENGINEERS PRODUCTION ENGINEERS ECONOMISTS LEGAL AND JUDICIAL BODIES

6 REVISITING THE COALBED METHANE RESERVOIRS IT IS NECESSARY TO UNDERSTAND: HOW METHANE IS STORED IN COAL? HOW CAN THIS STORED METHANE BE RELEASED EFFICIENTLY? AND ONCE IT IS RELEASED, HOW DOES THE METHANE FLOW TO THE WELL?

7 PENN STATE STRATEGY?????????

8 HOW DID WE FEEL AT THE ONSET??????????

9 PENN STATE STRATEGY ESTABLISHING FLOW MECHANISMS FIRST- GENERATION NUMERICAL MODELS SECOND- GENERATION NUMERICAL MODELS PRESSURE TRANSIENT ANALYSIS PROCEDURES TYPE CURVES FOR PRODUCTION ANALYSIS THIRD- GENERATION MODELS

10 EVOLUTION OF COALBED METHANE RESEARCH AT PENN STATE NO YES QUEST FOR UNDERSTANDING YES NO PURE BASIC RESEARCH RANDOM WALK RESEARCH USE INSPIRED BASIC RESEARCH PURE APPLIED RESEARCH CONSIDERATION OF USE

11 PENN STATE STRATEGY ESTABLISHING FLOW MECHANISMS FIRST- GENERATION NUMERICAL MODELS SECOND- GENERATION NUMERICAL MODELS PRESSURE TRANSIENT ANALYSIS PROCEDURES TYPE CURVES FOR PRODUCTION ANALYSIS

12 ESTABLISHING FLOW MECHANISMS DESORPTION DIFFUSION CONVECTION

13 DESORPTION KINETICS HENRY S ISOTHERM V E = VH p g V E LANGMUIR S ISOTHERM V E = VLpg p + p L g FREUNDLICHS ISOTHERM V E =Vf p n g P

14 DIFFUSION EQUILIBRIUM SORPTION MODELS: GAS ADSORBED IS ONLY A FUNCTION OF PRESSURE IN THE CLEAT NETWORK GAS DESORPTION IS INSTANTANEOUS GENERALLY PREDICTS OPTIMISTIC RESULTS NON-EQUILIBRIUM SORPTION MODELS: FREE AND ADSORBED GAS COMPOSITIONS ARE IDENTICAL, SELECTIVE ADSORPTION AND DESORPTION DO NOT OCCUR GAS TRANSPORT IN THE MICROPORES IS A DIFFUSION PROCESS SURFACE DESORPTION IS INSTANTANEOUS

15 NON-EQUILIBRIUM SORPTION MODELS PSEUDO-STEADY STATE dv dt = 1 [ V i - V E p λ i - ( )] " Similar to Warren and Root Approach " Relatively small computational work " Good for long term predictions UNSTEADY STATE " Most rigorous models (de Swaan s approach) " Require additional computational work " Good for all situations including short term

16 DIFFUSION MATRIX CLEAT NETWORK SLAB ELEMENTS

17 DIFFUSION MATRIX CLEAT NETWORK CYLINDRICAL ELEMENTS

18 DIFFUSION MATRIX CLEAT NETWORK SPHERICAL ELEMENTS

19 CONVECTION FACE CLEAT BUTT CLEAT

20 ESTABLISHING THE FLOW MECHANISM IN TIGHT FORMATIONS TWO FLOW FIELDS CONTROL THE GAS FLOW DYNAMICS : POTENTIAL FIELD MACROSCOPIC - DARCIAN FLOW p 1 r 1 p 2 r 2 r 1 = r 2 p 1 < p 2 CONCENTRATION FIELD RANDOM MOLECULAR - FICKIAN FLOW p 1 r 1 p 2 r 2 r 1 < r 2 p 1 < p 2

21 MULTIMECHANISTIC FLOW IS MULTIMECHANISTIC FLOW IMPORTANT? IN DOUBLE- POROSITY, SINGLE- PERMEABILITY SYSTEMS, MULTIMECHANISTIC FLOW DOMINATES WHEN 10-5 md < k < 10-1 md DIFFUSION FLOW DOMINATES DARCIAN FLOW DOMINATES

22 CHARACTERISTICS: MULTIMECHANISTIC FLOW DRIVE MECHANISMS EXERTED BY THE PRESSURE AND CONCENTRATION FIELDS ARE ACTING IN PARALLEL FLOW THROUGH PRESSURE FIELD OBEYS DARCY S LAW FLOW THROUGH CONCENTRATION FIELD OBEYS FICK S LAW NO CHROMATOGRAPHIC SEPARATION OF GAS TAKES PLACE DUE TO INDIVIDUAL DIFFUSIVITIES OF THE GAS CONSTITUENTS

23 PENN STATE STRATEGY ESTABLISHING FLOW MECHANISMS FIRST- GENERATION NUMERICAL MODELS SECOND- GENERATION NUMERICAL MODELS PRESSURE TRANSIENT ANALYSIS PROCEDURES TYPE CURVES FOR PRODUCTION ANALYSIS

24 FIRST GENERATION NUMERICAL MODELS BASIC CHARACTERISTICS: SINGLE-COMPONENT GAS SINGLE-PHASE OR TWO-PHASE DOUBLE-POROSITY, SINGLE-PERMEABILITY SINGLE-WELL, ONE-PHASE SINGLE-WELL, TWO-PHASE MULTI-WELL, TWO-PHASE MULTI-WELL, TWO-PHASE WITH MINING ACTIVITY

25 SINGLE-WELL MODELS CYLINDRICAL COORDINATES ELLIPTICAL COORDINATES STIMULATED VERTICAL WELL HORIZONTAL WELLS DRILLED FROM A SHAFT BOTTOM STIMULATED VERTICAL WELL

26 MULTI-WELL MODELS FRACTURED WELL HORIZONTAL BOREHOLE IMPERMEABLE BARRIER UNSTIMULATED WELL

27 MODEL PERFORMANCE GAS DESORPTION RATE, MSCF/DAY GAS PRODUCTION RATE, MSCF/DAY WATER PRODUCTION RATE, BBL/DAY TIME, DAYS

28 MODEL PERFORMANCE PRODUCED GAS, MSCF ACTUAL WELL HISTORY UNCONVENTIONAL GAS RESERVOIR MODELING CONVENTIONAL GAS RESERVOIR MODELING HISTORY MATCHING PREDICTION TIME, DAYS MARY LEE COAL SEAM

29 MODEL PERFORMANCE CONVENTIONAL GAS RESERVOIR APPROACH UNCONVENTIONAL GAS RESERVOIR APPROACH INITIAL GAS SATURATION MACROPORE PERMEABILITY POROSITY CRITICAL WATER SATURATION 60 % 9.0 md 82 % 0.1 % 0 % 2.0 md 3.1 % 30 %

30 PENN STATE STRATEGY ESTABLISHING FLOW MECHANISMS FIRST- GENERATION NUMERICAL MODELS SECOND- GENERATION NUMERICAL MODELS PRESSURE TRANSIENT ANALYSIS PROCEDURES TYPE CURVES FOR PRODUCTION ANALYSIS

31 PRESSURE TRANSIENT ANALYSIS I S O DIRECT PROBLEM INVERSE PROBLEM I x S O I O S

32 PRESSURE TRANSIENT ANALYSIS COAL SEAMS VS CONVENTIONAL RESERVOIRS PI Pwf t Coal Seam Conventional Reservoir q t

33 PRESSURE TRANSIENT ANALYSIS SHORTFALLS OF CLASSICAL WELL TEST MODEL FOR COAL SEAMS: DESORPTION DUAL POROSITY NATURE DEPENDENCE OF PERMEABILITY ON PRESSURE DIFFUSIONAL & LAMINAR FLOW

34 PRESSURE TRANSIENT ANALYSIS SOLUTION PROCEDURE : DIMENSIONLESS GROUPS LAPLACE TRANSFORMATION INVERSION NUMERICAL APPROXIMATE ANALYTICAL

35 PRESSURE TRANSIENT ANALYSIS SUMMARY OF SOLUTIONS DEVELOPED UNSTEADY-STATE SORPTION/DIFFUSION PSEUDO STEADY-STATE SORPTION/DIFFUSION NUMERICAL INVERSION APPROX. ANALYTICAL INVERSION NUMERICAL INVERSION FOR 6 POSSIBLE COMBINATIONS OF BOUNDARY CONDITIONS

36 PRESSURE TRANSIENT ANALYSIS Pressure, psi 2 ACTUAL PREDICTED Log (time), hr k md md φ τ 100 hr 90 hr V L 14.0 scf/cf 15.5 scf/cf

37 ESTABLISHING FLOW MECHANISMS PENN STATE STRATEGY FIRST- GENERATION NUMERICAL MODELS SECOND- GENERATION NUMERICAL MODELS PRESSURE TRANSIENT ANALYSIS PROCEDURES TYPE CURVES FOR PRODUCTION ANALYSIS

38 DECLINE CURVE ANALYSIS PATTERN RECOGNITION: THE DEVELOPED DECLINE CURVES PROVIDE A PRACTICAL TOOL WHICH CAN BE USED IN PREDICTING THE PERFORMANCE OF COAL SEAMS AND THEIR CHARACTERISTICS.

39 DEVELOPMENT OF TYPE CURVES EXPRESS TWO- PHASE EQUATIONS IN THE FORM OF A SINGLE RELATIONSHIP PUT THE EXPRESSION INTO A DIMENSIONLESS FORM GENERATE TYPE CURVES USING A NUMERICAL MODEL

40 TYPE CURVE FOR GAS FLOWRATE Dimensionless Gas Flow Rate S gi p p wf i = 70% = 0.2 r r w E E E E E E E+10 Dimensionless Time

41 TYPE CURVE MATCHING Dimensionless Time Gas Flow Rate (SCF/D) 1.0E E E E E E E E E+10 r w 1.0E r S gi p p wf i = 50% = Dimensionless Gas Flow Rate Time (Days)

42 DECLINE CURVE ANALYSIS TYPE CURVE MATCHING: EXAMPLE TYPE CURVE % CHANGE p (psi) p wf (psi) h (ft) S gi (%) V L (cc/gm) P L (atm) t (sec) 5.63 x x

43 ESTABLISHING FLOW MECHANISMS PENN STATE STRATEGY FIRST- GENERATION NUMERICAL MODELS SECOND- GENERATION NUMERICAL MODELS PRESSURE TRANSIENT ANALYSIS PROCEDURES TYPE CURVES FOR PRODUCTION ANALYSIS

44 SECOND GENERATION NUMERICAL MODELS BASIC CHARACTERISTICS: MULTI-COMPONENT GAS DOUBLE-POROSITY, DOUBLE-PERMEABILITY MULTI- COMPONENT GAS MULTI- MECHANISTIC FLOW MULTI-WELL

45 COMPOSITIONAL MODELING IS THERE A WIDE SPECTRUM OF COMPONENTS? ARE COMPOSITIONAL PHENOMENA DOMINANT? ADSORPTION/DESORPTION ISOTHERMS OF MULTICOMPONENT GAS MIXTURES ARE STRONGLY DEPENDENT ON GAS COMPOSITION COMPOSITION OF THE ADSORBED GAS IS SIGNIFICANTLY DIFFERENT FROM THAT OF THE FREE GAS

46 COMPOSITIONAL MODELING THERMODYNAMICS OF MIXED-GAS ADSORPTION IS ANALOGOUS TO VAPOR-LIQUID EQUILIBRIA: VAPOR FREE GAS LIQUID ADSORBED GAS

47 COMPOSITIONAL MODELING CALCULATION OF MIXED- GAS ADSORPTION FROM SINGLE- GAS ISOTHERMS: ADSORBED VOLUME CO 2 C 2 H 6 CH 4 N 2 TOTH ALGORITHMS UNILAN ADSORBED VOLUME PRESSURE PURE COMPONENT ISOTHERM PRESSURE MULTI-COMPONENT ISOTHERM

48 PENN STATE STRATEGY ESTABLISHING FLOW MECHANISMS FIRST- GENERATION NUMERICAL MODELS SECOND- GENERATION NUMERICAL MODELS PRESSURE TRANSIENT ANALYSIS PROCEDURES TYPE CURVES FOR PRODUCTION ANALYSIS ?

49 PENN STATE STRATEGY ESTABLISHING FLOW MECHANISMS FIRST- GENERATION NUMERICAL MODELS SECOND- GENERATION NUMERICAL MODELS PRESSURE TRANSIENT ANALYSIS PROCEDURES TYPE CURVES FOR PRODUCTION ANALYSIS INVERSE SOLUTION METHODOLOGIES UTILIZING SOFT COMPUTING PROTOCOLS COMPUTATIONALLY ENHANCED NUMERICAL MODELS

50 DEVELOPMENT OF AN EXPERT SYSTEM GENERATE A WIDE SPECTRUM OF FORWARD SOLUTIONS USING ANALYTICAL AND NUMERICAL TOOLS DEVELOPED CONSTRUCT ARTIFICIAL NEURAL NETWORK TOPOLOGIES THAT CAN BE USED FOR RESERVOIR CHARACTERIZATION AND PRODUCTION FORECASTING PURPOSES TRAIN THE ARTIFICIAL NEURAL NETWORK USE THE ARTIFICIAL NEURAL NETWORK FOR PREDICTION PURPOSES

51 POTENTIAL USES OF ARTIFICIAL NEURAL NETWORKS RESERVOIR CHARACTERIZATION PERMEABILITY POROSITY SORPTION CONSTANTS RELATIVE PERMEABILITY Field performance and field development parameters coal seam characteristics FIELD SCALE APPLICATIONS OPTIMIZED FIELD DEVELOPMENT VIRTUAL WELL TESTING PRODUCTION FORECASTING Coal seam characteristics and desired field performance optimized field development strategies

52 POTENTIAL USES OF ARTIFICIAL NEURAL NETWORKS a project screening tool USE OF THE DEVELOPED TOOLS IN ESTIMATING THE EXPECTED OUTCOME OF A CO 2 SEQUESTRATION PROJECT IN SHALE GAS AND COAL SEAM RESERVOIRS Coal seam or shale gas reservoir and CO 2 properties Prediction of CO 2 sequestration performance indicators

53 APPLICATIONS OF COMPUTATIONALLY ENHANCED NUMERICAL MODELS local grid refinement protocols

54 APPLICATIONS OF COMPUTATIONALLY ENHANCED NUMERICAL MODELS CO 2 sequestration in coal seams CO 2 Sequestration profiles 8.00E E E E E E+09 Rate, SCF/D 5.00E E E E E E+08 Amount, SCF 2.00E E E E E E Time, Days CH4 Production Rate CH4 Production Rate-Prim CH4 Cum Prod CO2 in place CH4 Cum Prod-Prim

55 APPLICATIONS OF COMPUTATIONALLY ENHANCED NUMERICAL MODELS CO 2 sequestration in shale reservoirs

56 PENN STATE S CONTRIBUTIONS: SUMMA RY MULTIMECHANISTIC FLOW CONCEPT IN TIGHT AND ULTRA-TIGHT SYSTEMS NUMERICAL MODELS WHICH TAKE INTO ACCOUNT FULL PHYSICAL DESCRIPTION OF THE FLOW DYNAMICS PTA PROCEDURES THAT CAN BE USED IN IN-SITU CHARACTERIZATION OF COAL SEAMS INCLUDING ITS SORPTION CHARACTERISTICS TYPE CURVES FOR TWO-PHASE RATE TRANSIENT PRESSURE TRANSIENT APPLICATIONS IN COAL SEAMS AND SHALE GAS RESERVOIRS

57 PENN STATE S FUTURE PLANS SUMMA RY USE OF THE DEVELOPED TOOLS IN CO 2 SEQUESTRATION APPLICATIONS USE OF THE DEVELOPED TOOLS IN OPTIMIZED PRODUCTION OF COALBED METHANE AND SHALE GAS RESERVOIRS

58 PENN STATE S REVISITING OF RESERVOIR ENGINEERING OF COLABED METHANE PRODUCTION HAS: EPILOG UE IMPROVED OUR UNDERSTANDING OF THE BEHAVIOR OF ADSORBED GASES ON COAL AT A MACROSCOPIC LEVEL PROVIDED A QUALITATIVE AND QUANTITATIVE UNDERSTANDING OF THE PHYSICS OF COAL/METHANE INTERACTIONS AND FLUID FLOW MECHANISMS IN COALBED RESERVOIRS ESTABLISHED A PLATFORM FOR TRAINING A NEW SCHOOL OF COALBED RESERVOIR SCIENTISTS AND ENGINEERS

59 EPILOGUE CBM RESERVE ESTIMATES VARY; HOWEVER A RECENT ESTIMATE FROM THE U.S. GEOLOGICAL SURVEY PREDICTS ALMOST 1,000 TRILLION CUBIC FEET OF METHANE WITHIN THE US. AT A NATURAL GAS PRICE OF US$3.00 PER THOUSAND SCF, THAT VOLUME IS WORTH US$3.0 TRILLION. AT LEAST 100 TRILLION CUBIC FEET OF IT IS ECONOMICALLY VIABLE TO PRODUCE. CBM CURRENTLY ACCOUNTS FOR NEARLY 10% OF U.S. ANNUAL GAS PRODUCTION AND APPROXIMATELY 12% OF ESTIMATED TOTAL U.S. NATURAL GAS RESERVES.

60 ACKNOWLEDGEMENTS GREGORY R. KING Ph.D DAVID J. REMNER M.S JAMES E. KOLESAR M.S WONMO SUNG Ph.D 1987 KEMAL ANBARCI Ph.D1991 SHAHAB MOHAGHEGH Ph.D 1992 ADWAIT CHAWATHE Ph.D1995 JULIO MANIK Ph.D 1999 TIMOTHY E. KOHLER Ph.D1999 XIULI DONG M.S OLUFEMI ODUSOTE M.S BURCU GORUCU M.S KARTHIK SRINIVASAN M.S PROB THARAROOP Ph.D VAIBHAV RAJPUT M.S DENNIS ALEXISPh.D ERHAN ASLAN Ph.D. 2013