Enhanced recovery

Optimizing the Use of Miscible Injectant at the Greater Prudhoe Bay Fields

This paper provides an overview of all enhanced-oil-recovery (EOR) projects in the Greater Prudhoe Bay (GPB) region and presents the process and methodology for MI allocation to these projects and to individual injection patterns.

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Source: Getty

Miscible injectant (MI) has been used at Prudhoe Bay and its satellite fields for more than 30 years. This paper provides an overview of all enhanced-oil-recovery (EOR) projects in the Greater Prudhoe Bay (GPB) region and presents the process and methodology for MI allocation to these projects and to individual injection patterns. A new approach is used to determine the amount of MI allocated to each project on the basis of predicted marginal MI use per barrel of EOR oil.

Introduction

The MI-gas EOR process at Prudhoe Bay began in late 1982. In late 1986, the Central Gas Facility (CGF) began operation, enabling the first field-scale EOR project, the Prudhoe Bay Miscible Gas Project (PBMGP), to start in early 1987. Since then, the PBMGP has expanded to more than 170 injection patterns in the main field of Prudhoe Bay. Fig. 1 provides a layout of the oil fields on the North Slope of Alaska.

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Fig. 1—Area map of Alaska North Slope.

 

The CGF is a gas-processing plant that makes natural-gas liquids (NGLs) for shipment in the Trans-Alaska Pipeline System and MI for EOR projects. The CGF currently processes an annual average of approximately 7.5 billion scf/D of produced gas to generate approximately 40,000 STB/D of NGL and more than 200 million scf/D of MI. The feed gas comes from three different sources—solution gas from the produced oil, free reservoir gas from the gas cap, and returned MI (RMI) that was previously injected into the reservoir. The total amount of MI produced at the CGF is the sum of the fresh MI (which can be forecast by the GPB full-field simulation model) and the recaptured RMI (which can be forecast by COBRA and process modeling). COBRA is a full-field scaleup tool for predicting MI performance on the basis of type-pattern-simulation-model results.

MI gas produced at the Prudhoe Bay CGF is a rich gas composed primarily of carbon dioxide (approximately 21%), methane (approximately 32%), ­ethane (20%), propane (25%), and a small amount of butane and heavier components (approximately 2–3%).

Most of the GPB EOR projects are pattern floods that use a water-alternating-gas (WAG) injection to improve areal and vertical sweep efficiencies.

EOR-Performance Analysis

EOR-Benefit Evaluation in Producers. The historical EOR oil benefit from each producer can be estimated through decline-curve analysis. For conventional WAG patterns, the incremental benefit from MI injection is evaluated using an approach modified from the ­multiple-trend-forecasting technique. Water/oil ratio (WOR) is plotted on a log scale vs. recovery factor on a Cartesian scale to estimate the effect of MI injection on WOR. A WOR trend of water­flood is established by matching the WOR before MI injection to a waterflood type curve, which is generated from a ­reservoir-simulation model. This hypothetical WOR trend is compared with the actual historical data, and any suppression of WOR from the type curve is attributed to the effect of MI injection.

RMI Estimation in Producers. In the GPB fields, produced-gas samples normally are taken quarterly for active MI-injection patterns. The Prudhoe Bay Unit Laboratory analyzes these samples and enters the compositions into a local database. The rate of RMI is automatically calculated on the basis of these compositions as well as measured oil- and gas-production rates.

Allocation of EOR Oil and RMI to Injectors. WAG injection is managed at injectors by swapping between water and MI services and controlling the injection rates of water or MI; therefore, field-performance data need to be allocated to injector-centered patterns. A dynamic production-allocation factor is used to allocate the production rates of EOR oil and RMI back to injectors.

Pattern Ranking. After the RMI and EOR data are allocated to injector-­centered patterns, the patterns can be ranked on the basis of one or more of the following criteria:

  • Pattern maturity as measured by cumulative hydrocarbon pore volume of MI injected
  • Pattern maturity as measured by instantaneous RMI/MI ratio
  • Pattern efficiency as measured by cumulative MI use (Mscf/STB)
  • Combination of maturity and efficiency

Pattern maturity is a measure of how mature a pattern is compared with the project design. Another measure of pattern maturity is the ratio of RMI to MI injected (RMI ratio). The RMI ratio increases as a pattern becomes more mature, indicating that the MI injected is mobilizing less EOR oil.

Performance Prediction

A holistic MI-use strategy must account for the past performance and the predicted performance of the EOR patterns. MI EOR performance in GPB is predicted using COBRA models.

Introduction to COBRA. COBRA is a full-field forecasting tool for waterflooding and miscible-gas injection based on type curves developed using numerical-simulation models.

The basic building block of COBRA is an injector/producer segment. The entire modeled region is divided into injector/producer segments. Production from each segment is governed by user-supplied performance curves.

Fresh MI supply, RMI imported from other fields, and MI exported to other fields can all be entered into COBRA, which calculates the amount of MI available to inject for the subject field on the basis of these inputs and the RMI from the same field. The RMI and EOR-oil-production rates are predicted on the basis of previous MI-injection rates using EOR mobilization curves and timing functions. All patterns are ranked at each timestep on the basis of EOR efficiency, with MI preferentially allocated to the best patterns until all available MI is used.

GPB COBRA Models. A COBRA model has been developed for each of the current EOR projects in GPB. History matching is performed to match the observed field performance at the field level. Performance prediction at the field level is more accurate than at the pattern level because allocation errors are canceled out, as long as the performance curves are representative of the average field performance.

Each COBRA model (other than the PBMGP model) is run independently to predict the EOR and RMI performance of the project with a predetermined amount of MI supply. The PBMGP COBRA model is then used to predict EOR and RMI performance of the PBMGP patterns, as well as the total amount of MI available for all GPB projects, on the basis of

  • CGF fresh MI supply predicted by the Prudhoe Bay full-field model
  • The MI exported to all other projects outside PBMGP
  • The RMI from all EOR projects, including PBMGP

MI Allocation

MI-Allocation Strategy. The objective of MI allocation is to optimize EOR oil production economically across all GPB projects within operational constraints. Ideally, all EOR patterns in GPB would be ranked together in the same way, and MI would be allocated preferentially to the highest-ranked patterns. Practically, however, it is often more effective to rank patterns in each project independently, considering the time required to update the more than 300 injection patterns. Hence, MI allocation in GPB is hierarchical; first it is performed at the project level, then at the pattern level.

At the project level, the amount of MI allocated to each project is determined by using a uniform cut-off MI-use value across GPB. Within a project, all ­injector-centered patterns are ranked on the basis of their maturity and MI use. MI is allocated to the ­highest-ranked patterns until the amount of available MI is consumed for that project. New patterns are always ranked favorable until sufficient performance data are available.

Another consideration when allocating MI is that some projects produce more RMI than others. For this reason, when comparing MI use among projects, net MI use is used instead of gross MI use.

MI-Allocation Process. GPB MI is allocated to various MI projects and injection patterns according to the following procedure:

  • Analyze field performance of each producer, and allocate EOR oil and RMI produced to injection-centered patterns.
  • Rank injection patterns on the basis of pattern maturity and gross MI use within each project.
  • History match the COBRA model of each project against field performance at least at the field level.
  • Run each COBRA model at various MI-supply rates to determine net MI use as a function of MI-supply rate.
  • Determine the cut-off value of net MI use on the basis of total amount of MI available at GPB.
  • Determine ideal MI rate to each project on the basis of the cut-off value of net MI use.
  • Allocate MI to all new projects on the basis of the designed MI rates until field-performance data are available.
  • Operational constraints are then applied to determine the actual MI allocation to each EOR project across GPB.

The actual MI-injection target for each project is determined on the basis of the project’s injection capacity, the theoretical optimal MI target, and the predicted total MI available for GPB. Operational constraints will also be considered in field implementation of these targets. This process is repeated quarterly to account for changes in reservoir maturity, seasonal effects on MI-production rate, and operational constraints.
This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 180420, “Optimizing the Use of Miscible Injectant at the Greater Prudhoe Bay Fields,” by S.X. Ning, SPE, B.S. Jhaveri, E.M. Fueg, SPE, G. Stechauner, J.L. Jemison, SPE, and T.A. Hoang, BP Exploration (Alaska), prepared for the 2016 SPE Western Regional Meeting, Anchorage, 23–26 May. The paper has not been peer reviewed.