Increasing Production in a Mature Basin: "The Choke Model"
Authors: Palen W. , Goodwin A. 
Published: December 2007

British Petroleum issued a challenge, in 1993, to its European producing assets, to increase production by 15% while keeping within its agreed capital budget. To compliment new production attention was also focused on increased production efficiency. The resultant production efficiency campaign, based on simple premises. has contributed a 4% real increase in the operations efficiency in BP's North Sea portfolio, without a substantial increase in opex or capex, resulting in a net gain to BP of some 10 mmboe over the last two years.

Introduction

The North Sea has become a mature province even as its production level continues to rise. British Petroleum recognized the aging nature of its portfolio and issued a challenge to its producing assets, in 1993, to increase production by 15% while keeping within its capital and opex forecast. To compliment the work that was focusing on increasing Production Potential, (more reserves, more wells and more production capacity) attention was also focused on Production Efficiency. The production efficiency campaign was coincident with a reorganization into distinct asset teams, which placed a premium both on safe production delivery within, and communication between assets. To benefit the challenge a common language for defining production losses was adopted and modified to be generic enough for all assets to use. The resultant "choke model" has become the tool that has allowed alignment of problem identification and actions, both intra asset and between like assets. Within two years of adopting the model the assets have been able to show marked and near continuous improvement in both their production efficiency and the delivery of hydrocarbons to market.

Statement of Theory and DefinItions

Production Efficiency improvement is built around the simple concept of a pipeline through which the oil flows from reservoir to market. The objective is maintaining the daily flow rate at the maximum possible. This throughput may be plant capacity for plateau producers or the total well potential for mature phase fields. See Figure 1 Generic Choke Model Concept. A series of restrictions or chokes are visualized in this pipeline, that represent the areas of production loss, i.e. Reservoir potential, as measured by well tests, that is not delivered. The resultant losses are those that occur due to:Reservoir Management;Well Availability and Utilization;Topsides Availability and Utilization, (i.e. the efficiency of using the available equipment); andExport system.

(A more specific calculation procedure for the chokes, as given to the assets in 1993, is detailed in the appendix.) These are simplified for management reporting as Reservoir, Wells, Plant, and Export chokes. At this level of detail these "chokes" are common to all our assets.

The choke model exists on lower levels as seen in Table 2, Expanded Choke Model Example. Items that appear as in parentheses in the table are specific only to the gas business where the concept of loss must be redefined to allow for system substitution, where available. Thus a gas asset suffers only a true loss when it has missed a DCQ target and has not been able to make up its temporary shortfall. In most instances a pure gas asset carries both a sales efficiency, near 100%, and a system or platform efficiency that more accurately describes the state of the operations. Assets that are both significant oil and gas producers, e.g. Bruce, carry two sets of efficiencies, one as a gas producer and one as an oil producer.

The chokes may become more numerous depending on the reservoir processes employed by the asset. This is illustrated in Table 1 as one reads down the figure. In a field such as Magnus or Ula the Gross Potential is very dependent on water injection capacity, and a separate choke model can be used to model injection performance on the wells and reservoir potential. Some assets will carry analysis to the six minor chokes shown and all will further analyze down to at least another level e.g. ESP failure, metering. The assets modify/use the lower parts of the model they see as valid for their particular circumstances.

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