Tiorco

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Published on January 2, 2008

Author: aksu

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Simulation of Polymer Gel Injection Well Treatments:  Simulation of Polymer Gel Injection Well Treatments Chuck Norman Tiorco, Inc. Tiorco de Argentina Agenda:  Agenda Flood-Out Waterflood Model Input Model Process Information Generated by the Waterflood Model Flood-Out Polymer Gel model Dykstra-Parsons Theory Information generated by the Gel Model Forecasts with the Gel Model (Examples) Slide4:  ABILITY TO CONTROL LAYER PROPERTIES ACCORDING TO IN-SITU CHEMICAL CONCENTRATIONS: RESERVOIR (TOTAL) ADSORBED (IMMOBILE) MOBILE (PRODUCIBLE) What data entry is required?:  What data entry is required? MANDATORY – PVT & reservoir data What data entry is required?:  What data entry is required? MANDATORY – model layers NOTE: MORE LAYERS RESULT IN IMPROVED FORECASTING RESOLUTION AS EACH LAYER CONTRIBUTES ONE “POINT” IN THE TYPE-CURVE What data entry is required?:  What data entry is required? MANDATORY – production profiles What data entry is required?:  What data entry is required? OPTIONAL – log layers The flood-out Process:  The flood-out Process 01 Import fine resolution log data and define coarse model layers - 02 Create coarse model layers - The flood-out Process:  The flood-out Process 03 Generate forward model pseudo-relative permeability - 04 Generate forward model fractional flow - The flood-out Process:  The flood-out Process 05 Generate the forward model production type-curve - 06 View the first-pass water-cut history match (match needs improvement) - First-pass: Poor history match! The flood-out Process:  The flood-out Process 07 Generate reverse model fractional flow - 08 Generate reverse model pseudo-relative permeability - The flood-out Process:  The flood-out Process 09 Generate the reverse model “Eglew” layers - < New Versus Old > < New Versus Old > The flood-out Process:  The flood-out Process 11 Generate a new forward model fractional flow - 12 Generate a new forward model production type-curve - 10 Generate a new forward model pseudo-relative permeability - The flood-out Process:  The flood-out Process 13 An improved water-cut history match results from importation of the reverse model into the forward model - 14 An optimised production and injection forecast can now be generated within system’s constraints - The flood-out Process:  The flood-out Process 15 Create a flood-out slide show and generate synthetic logs - 16 forecast production and injection by multi-cell material balance - Dykstra-Parsons’ Water Flood Theory adapted to Chemical Flood Modeling:  Dykstra-Parsons’ Water Flood Theory adapted to Chemical Flood Modeling DYKSTRA-PARSONS’ THEORY: (a) is applicable for all mobility ratios (b) assumes layers flood-out in flow- velocity order (c) layer cross-flow does not occur Polymer Flood Model: How does it work?:  Polymer Flood Model: How does it work? Dykstra-Parsons’ theory is employed to accomplish the following (at each time step) for a user-specified set of Model Layers: Determine relative flood-frontal advancement for each layer Generate a type-curve (Oil Recovery Factor versus Water-cut), which is interpolated by the forecasting optimiser Once polymer is introduced, layer permeability is altered according to resistance factor expressed as a function of in-situ (i.e. reservoir) polymer concentration (ppm) Highly-permeable layers accept larger water injection volumes, and consequently polymer concentration builds-up preferentially in these layers. This stabilises the flood, or invokes profile conformance. Dykstra-Parsons’ Water Flood Theory adapted to Chemical Flood Modelling:  Dykstra-Parsons’ Water Flood Theory adapted to Chemical Flood Modelling A spreadsheet employing non-linear regression automatically finds a cubic polynomial of best-fit to tabulated data HOW DOES IT WORK? High K Layers build-up the highest polymer concentration, which alters layer flow-velocity order and invokes profile conformance. Note: THIS CURVE APPLIES FOR A FIXED INJECTION RATE IN-SITU POLYMER CONCENTRAION RESISTANCE FACTOR Polymer Gel Model Output and Forecasts:  Polymer Gel Model Output and Forecasts Slide21:  In this example, polymer is injected over a three month period: Month1 – 500 ppm Month2 – 1000 ppm Month3 – 1500 ppm in-situ or reservoir polymer concentration produced polymer concentration Re-commence “pure” water injection adsorbed polymer concentration Slide22:  Produced polymer concentration – high permeability layers are produced preferentially in-situ or reservoir polymer concentration Polymer injection “flag” adsorbed polymer concentration Zoomed view of “production side” NOTE that the adsorbed polymer concentration dilutes once “pure” water injection re-commences Slide23:  Produced water rate decreases due to polymer injection Oil rate increases due to polymer injection Production response to the polymer flood Actual Water Injection Rate (AWIR) is optional User input Slide24:  Once polymer injection ceases, displaced by “pure” water injection, the resistance factor decreases. Adsorbed polymer is entrapped in order to model residual resistance. Resistance Factor > Re-commence “pure” water injection Slide25:  Average Permeability changes with in-situ polymer concentration Re-commence “pure” water injection Slide26:  Maximum permeability of all model layers Average permeability and standard deviation of model layer permeability NOTE: standard deviation of K is a measure of profile conformance, enhanced by the injection of polymer (i.e. Std Dev. decreases once polymer is introduced) Slide27:  Commence polymer injection Mobility Ratio “M” decreases as the flood front stabilises Mobility Ratio “M” increases as the in-situ polymer concentration dilutes (i.e. post-polymer flood) WOR: water flood (base case – left) versus polymer flood (right):  WOR: water flood (base case – left) versus polymer flood (right) “BEFORE” AND “AFTER” PRODUCTION PERFORMANCE - Reduced WOR due to polymer injection Base Case Water-flood Oil Rate: water flood (base case – left) versus polymer flood (right):  Oil Rate: water flood (base case – left) versus polymer flood (right) “BEFORE” AND “AFTER” PRODUCTION PERFORMANCE - Oil rate uplift due to polymer injection Base Case Water-flood Slide30:  The Polymer Flood Model allows the User to track the performance of any Model Layer – here and in the following slides layer # 20 performance is shown. Dykstra-Parsons relative layer water flood penetration distance (versus time) for layer # 20 Layer # 20 100% flooded Slide31:  Produced polymer concentration in-situ or reservoir polymer concentration Polymer injection “flag” adsorbed polymer concentration Polymer production (at the producing well) only commences once the layer has 100% flooded (according to Dykstra-Parsons’ Theory) – prior to layer-by-layer water breakthrough each layer produces clean oil into the producing well. Slide32:  Layer # 20 Oil Rate increases as the model allocates more Water Injection to layer # 20 (i.e. following the commencement of polymer injection) Layer # 20 100% flooded Water breakthrough at producer for layer # 20 Slide33:  Once polymer injection ceases, displaced by “pure” water injection, the resistance factor decreases. Adsorbed polymer is entrapped in order to model residual resistance. Layer # 20 Resistance Factor > Re-commence “pure” water injection Slide34:  Layer # 20 Permeability changes with in-situ polymer concentration Re-commence “pure” water injection Simulation of Polymer Gel Injection Well Treatments:  Simulation of Polymer Gel Injection Well Treatments Chuck Norman Tiorco, Inc. Tiorco de Argentina

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