Research advisor: Dr. Thomas W. Engler Committee members: Drs. Mike Kelly and Reid Grigg

Transcription

1 Research advisor: Dr. Thomas W. Engler Committee members: Drs. Mike Kelly and Reid Grigg Presented by Akapak Nick Srichumsin Graduate Student New Mexico Tech 1

2 Introduction Reservoir characterization Model construction History matching Prediction Conclusions 2

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4 This research is one part of the project entitled Mini-Waterflood: A New Cost Effective Approach to Extend the Economic Life of Small, Mature Oil Reservoirs. The project focuses on assisting small producers with technical knowledge to enhance oil recovery for a mature oil field. Core Analysis Reservoir Characterization Reservoir Simulation Evaluation of Mini-Waterflood Potential 4

5 The targeted reservoirs are small, mature, shallow, low pressure, low temperature, and has unfavorable mobility. Typically ignored, this type of reservoir generally still contains significant amount of oil-in-place. Round Tank Fields with high oil production have experienced waterflood. 5

6 The main objective of this thesis is to evaluate the waterflood potential of the Round Tank (Queen) reservoir and determine the best strategy for the field by using reservoir simulation. 6

7 Chaves County Roswell Queen Vest Ranch Caprock New Mexico Texas Double L S Lucky Lake Round Tank High Lonesome Sulimar Lea County Miles Eddy County Goat Seep reef Carlsbad Hobbs Delaware Basin 0 12 miles The Round Tank Queen sand Thin reservoir (~16 thick). Stratigraphic trap ~1,500 from the surface 7

8 Gp = 4.2 Bscf Pi = 600psi P ~ 50psi RF ~ 92% Np = 26 MBO OOIP = 2.85 MMBO RF ~ 1% 8

9 Gas properties Dry gas w/ high N 2 (61% N 2 and 28% CH 4 ) Oil properties Dead oil (very low GOR) 35 API w/ 13.67cp 9

10 To locate injectors along the downdip edge of the oil column in the water leg, and producers along the updip edge of the oil column. 10

11 Data Acquisition Data Interpretation Reservoir Characterization Model Construction Model Validation Reservoir Simulation Prediction 11

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13 A common problem in small, mature fields is the limited and poor quality data, typically consisting of only old logs and production history. Evaluation of the field relies on existing data or data which are easy to acquire. Old logs (circa 1960s), 14 modern logs and one-core are the main sources for this reservoir study. 13

14 Available wireline logs for acquiring porosity Modern logs (late 2000s) a combination of density and neutron logs. Old logs (1960s to 1970s) Neutron Sonic Density In general, only one type is available at each well location. The main problems applying old logs are (1) the poor quality and reliability and (2) the required conversion. 14

15 Anhydrite layer Maximum porosity interval Anhydrite layer Density/neutron crossplot 15

16 A common problem for the old neutron log is the units; generally, CPS or API unit was used. Typically, these units can be converted to porosity unit (either % or fraction) with the use of calibration chart provided by a logging company. Different in operating companies, scale ranges, borehole conditions, and calibration Calibration chart (courtesy Schlumberger) If the proper calibration chart is not accessible, a linear relationship of tool response and porosity can be created from two known, porosity control points. 16

17 All the neutron logs with various scale-ranges were normalized into 0-1 scalerange with a linear relationship. Min. Ф interval Control point 1 Ф = 1% Max. Ф interval Control point 2 Ф = 23.4% (from Modern logs) 17

18 Two linear relationships were made: (1) Linear porosity vs. linear tool response (2) Log porosity vs. linear tool response (1) Adjacent wells (2) 18

19 Advantages The normalizing process helps to mitigate the effects of the different conditions among wells such as hole size, mud type, and logging company. The proposed application, therefore, improves unreliable and poor quality data to useful and reliable data. 19

20 Ф Hi t & Mod t > 29% Porosity-transform correlations Wyllie s transform - Clean and consolidated formation Raymer-Hunt transform - Unconsolidated/friable formations Wyllie s and Raymer-Hunt transforms (courtesy Schlumberger) 20

21 Adjacent well Raymer-Hunt Raymer-Hunt transform is not applicable within the Round Tank Queen formation. Raymer-Hunt Adjacent wells 21

22 Unconsolidated sands from Gulf of Mexico do not comply with the Raymer-Hunt transform; the actual porosities from core experiment tend to be lower than calculated. Comparison between Raymer-Hunt transform with Gulf of Mexico data obtained from moderately consolidated to unconsolidated sands (Bassiouni 1994) 22

23 In general, abnormally high interval transit time is due to the effect of reservoir gas and uncompacted formation. Main factor causing abnormally high t Core samples collected from Round Tank Queen Unit No.6-Y indicate friable characteristic of the formation. 23

24 Overestimated porosities due to the effect of friable sand need to be corrected. The work was done by modifying Raymer-Hunt transform with the correction factor, an Uncompaction Correction (Uc). Uc is the ratio of apparent sonic porosity to known porosity. R t C log t t log ma Raymer-Hunt transform C = 0.6 for gas zone, C = 0.67 for oil and water zones tma = 56 μsec/ft for sandstone formation U c R(max) known(max) Raymer-Hunt Trans. Adjacent new wells ' R U R c Modified Raymer-Hunt transform 24

25 Comparison between modified Raymer-Hunt transforms with Gulf of Mexico data obtained from moderately consolidated to unconsolidated sands The proposed procedure gives satisfactory results in both value and curve trend. 25

26 Water saturation of the field was observed through well logs with the use of Archie s equation. S w FR R T w 1/ n F a m Where a = tortuosity factor m = cementation exponent n = saturation exponent 26

27 Resistivity/porosity crossplot or Pickett plot is applied for this study to examine m and n exponents. 27

28 Hydrocarbon zone w/ Siw =41.7% (from core Siw =43%) c OWC (~2210 ) Transition zone FWL (???) 28

29 Capillary pressure curve was constructed based on published correlation and log-derived water saturation. The power function proposed by Brooks and Corey (1964) is applied to create Pc curve. Pc curve can be converted to height curve by height p c w o p c S p d ' 1/ w S ' w S 1 S w S orw iw S iw where λ = pore-size distribution index. P d = entry pressure S w = normalized water saturation 29

30 Layers of the Round Tank Queen Sand need to be identified to acquire accurate definition of the geologic flow units within the sand. A stratigraphic layering approach was chosen to identify the number of layers and layer thicknesses. 30

31 Evidence of abnormally high responses from sonic logs indicates that a friable zone exists with the Queen sand. The observation of friable zone was made by focusing on two dimensions areal and vertical. Areal Vertical Highest over-response 31

32 A core sample from Round Tank Queen Unit No.6-Y also supports that Layer3 is the most friable interval. 32

33 Mineralogy of the Round Tank Queen sand has been studied through examination of core samples and interpretation of wireline logs. Thin section study from core samples (Wilson 2010) The main mineral is quartz, mixed with potassium feldspar, anhydrite, micas, and illite. 33

34 Depth, ft Mineralogy analysis through wireline logs Mineralogy analysis was made by using density/neutron crossplot and lithodensity MID plot. Example from Eskimo State No True Porosity, frac. Density/neutron crossplot Lithodensity MID plot The Queen Interval 34

35 Mineral identification chart (courtesy Schlumberger) The result supports the core analysis about clay types. Thorium/potassium ratios (Th/K) are quite consistent among layers (~1.7 Th/K). 35

36 Because the formation is characterized into 2 zones, friable and consolidated, two porosity/permeability correlations are applied. Adjacent field core experiment (the Sulimar Queen and South Lucky Lake fields) Round Tank Queen core experiment (taken from samples located in the friable zone) 36

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38 To achieve the main objective of the study, the following approaches are selected for constructing the simulation model: Actual, full-field model with three-dimension aspect. Isotropic permeability with a single porosity system. Black-oil fluid description (Eclipse E100 is used for the study). Fully-implicit equation solver. 38

39 No sensitivity analysis of gridblock number has been made on this study. A rule of thumb mentioned in Ertekin (2001) is applied; 3-5 gridblocks between production wells. The shortest distance between wells (L) L Gridblock size (WxL) = L/5 x L/5 39

40 To accurately construct the model, coverage of friable zone need to be considered. Areal Vertical Consolidated Friable Consolidated Friable Consolidated Friable Porosity map of Layer3 before corrections of friable effect 40

41 Geologic Description - Structure - Porosity - Permeability Fluid PVT Properties - Dead oil - Dry gas - Water Petrophysics - Pc curve - Kr curves 3D-Blackoil simulation model 41

42 10% Porosity cut-off for reservoir boundary 42

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44 Reservoir pressure, well production and bottomhole flowing pressure are the three parameters for history matching. Assumption: All the wells, especially oil wells, were operated with low bottom hole pressure. Production rates were used in the model to constrain operating conditions when running the simulation. Reservoir pressure Model Validation Well production Bottomhole flowing pressure 44

45 The decline curve analysis from Fetkovich (1996) type curve indicates that most gas wells had produced with constantly low bottom hole pressure. JW-State#2, b=0.5 Mehurin#3, b=0.5 45

46 Before history matching JW-State#2 After history matching (manual history-matching approach was applied) JW-State#2 46

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48 60% Reduction 60% Reduction 30% increased for kro 75% Reduction The large reduction indicates that permeability in the Round Tank Queen field is significantly lower than the other Queen sands. 48

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50 The proposed flooding pattern is to locate injectors along the downdip edge of the oil column in the water leg, and producers along the updip edge of the oil column. The pattern design, well locations and spacing, strongly depends on the existing new wells in the field to reduce the cost of infill drilling. The pattern consists of 6 producers and 6 injectors. 50

51 The prediction was performed by running the simulation for 20 years. Injection and production rates were controlled by bottomhole flowing pressures. All production wells produce with the minimum bottomhole flowing pressure. The maximum bottomhole pressure for injection wells is limited at fracture pressure. The prediction results show extremely poor water injection and oil production. - Prediction results - Field injection and production rates Injection rate ~3.5 BWPD/well Production rate ~1.33 BOPD/well 51

52 The observation of oil saturation and reservoir pressure through time indicates the poor waterflooding performance - slow flood front movement and unable to fill-up reservoir pressure. 52

53 Reservoir properties and water injection rates of the Round Tank Queen field were compared with the successful waterflooding field, the Sulimar Queen. Water injection rates were calculated from radial-flow, steady-state equation with various differential pressures (dp). q w kk B w w rw ln( r h( P e / r w wf P ) S R ) Many factors contribute to the low injection rate of the Round Tank Queen field such as low permeability, low krw and low differential pressure. 53

54 Indication of the poor transmissibility of the formation. - Prediction results - Field injection and production rates Injection rate ~3.5 BWPD/well Production rate ~1.33 BOPD/well 54

55 Low production and injection rates would also be influenced by high oil viscosity. 55

56 An influence of the depleted reservoir pressure to waterflooding performance was also investigated. The observation of pressure fill-up trend was made by running the simulation without opening any producers. Shut-in all producers Small pressure increase in oil and water zones; approximately 150 psi of pressure is increased for 20 years of water injection. 56

57 The investigation was further made by multiplying permeability of the model with a factor of 10 and reduce μ o to 7 cp to reduce the effect of poor transmissibility. 10xPermeability and 7 cp oil viscosity Water inj. Oil prod. Water prod. Even at higher injection rate and better formation transmissibility, pressure fill-up is still unfavorable. Significant amount of oil moves up into the gas cap due to water displacement. The proposed flooding pattern seems not to be effective. 57

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59 Successful characterization of the Round Tank Queen reservoir with limited and poor quality data was made with the assistance of modern logs and core analysis. Normalization of old neutron logs and calibration of old sonic logs were two techniques applied to acquire valuable information. The study of mineralogy indicates that quartz is the main mineral of the formation with other minor minerals present a combination of potassium feldspar, anhydrite, micas and illite. A newly discovered friable sand bed was identified and has implications on reservoir performance. The results from history matching show satisfactory outcomes; a minor adjustment was made for the porosity distribution, and reservoir boundary was identified. 59

60 The large permeability reduction from history matching indicates that permeability of the Round Tank Queen formation is significantly lower than the other Queen sands. The prediction results of the proposed flooding pattern show poor performance: low oil production and water injection rates, slow flood front movement and unable to fill-up reservoir pressure. Many factors contribute to the poor performance including low permeability, high oil viscosity, depleted gas-cap and low differential pressure between bottomhole and reservoir. 60

61 Research Partnership to Secure Energy for America (RPSEA) Dr. Thomas W. Engler Drs. Mike Kelly and Reid Grigg Drs. Her-Yuan Chen and Robert E. Bretz Armstrong Energy and Bruce Stubbs Garrett A. Wilson, Albert Ofori, and Oluwafemi Oduye Karen M. Balch 61

62 Q&A 62

63 Backup 63

64 M ' krw' o kro' w Round Tank Queen Sulimar Queen krw' uw kro' uo M'

65 Model discretization is the process of dividing space and time of the simulation model into discrete segments. Space discretization gives information about grid-number needed for horizontal and vertical directions whereas time discretization provides the timesteps used in the model. 65

66 Space Discretization Vertical discretization (layering) As stated previously, the Round Tank Queen sand can be divided into three layers based on gamma ray logs. Time Discretization (Timesteps) Timesteps are placed on any major well history occurred such as 1st production, shut-in, and workover. Timesteps from all the wells are placed on yearly intervals, and all the wells share the same timestep (Jan 1 of every year) for simulator computation. 66

67 No sensitivity analysis of gridblock number has been made on this study. A rule of thumb mentioned in Ertekin (2001) is applied; For primary recovery, 3-5 gridblocks between production wells. For waterflooding recovery, 5-10 gridblocks between adjacent wells. > 10 Gridblocks The shortest distance between wells (L) L Gridblock size (WxL) = L/5 x L/5 67