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Stochastic analysis and finance and insurance and risk
Publications

Haavardsson, Nils Fridthjov; Huseby, Arne; Pedersen, Frank; Lyngroth, Steinar; Xu, Jingzhen & Aasheim, Tore (2010). Hydrocarbon Production Optimization in Fields With Different Ownership and Commercial Interests. SPE Reservoir Evaluation and Engineering.
ISSN 10946470.
13(1), s 95 104 . doi:
10.2118/121399PA
Show summary
A main field and satellite fields consist of several separate reservoirs with gas cap and/or oil rim. A processing facility on the main field receives and processes the oil, gas, and water from all the reservoirs. This facility is typically capable of processing only a limited amount of oil, gas, and water per unit of time. In order to satisfy these processing limitations, the production needs to be choked. The available capacity is shared among several field owners with different commercial interests. In this paper, we focus on how total oil and gas production from all the fields could be optimized. The satellitefield owners negotiate processing capacities on the mainfield facility. This introduces additional processingcapacity constraints (booking constraints) for the owners of the main field. If the total wealth created by all owners represents the economic interests of the community, it is of interest to investigate whether the total wealth may be increased by lifting the booking constraints. If all reservoirs may be produced more optimally by removing the booking constraints, all owners may benefit from this when appropriate commercial arrangements are in place. We will compare two production strategies. The first production strategy optimizes locally, at distinct time intervals. At given intervals, the production is prioritized so that the maximum amount of oil is produced. In the second production strategy, a fixed weight is assigned to each reservoir. The purpose of the weights is to be able to prioritize some reservoirs before others. The weights are optimized from a lifecycle perspective. As an illustration, a case study based on real data is presented. For the examples considered, it is beneficial to lift the booking constraints because all of the reservoirs combined can be produced more efficiently when this is done.

Huseby, Arne & Haavardsson, Nils Fridthjov (2010). Multireservoir production optimization under uncertainty, In Radim Bris; Sebastián Martorell & C. Guedes Soares (ed.),
Reliability, Risk and Safety. Theory and Applications.
CRC Press.
ISBN 9780415555098.
Volume I.
s 407
 413
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Oil and gas production from several reservoirs are often processed at a single processing facility. Due to limitations in the processing capacity, this implies that the production rates from the individual reservoirs have to be reduced. That is, for each reservoir the production rate is scaled down by a suitable choke factor between zero and one, chosen so that the total production does not exceed the processing capacity. Recent studies of production optimization include (Horne, 2002), (Merabet & Bellah, 2002) and (Neiro & Pinto, 2004). (Huseby & Haavardsson, 2009) introduced the concept of a production strategy, a vector valued function defined for all points of time t ≥ 0 representing the choke factors applied to the reservoirs at time t. As long as the total potential production rate is greater than the processing capacity, the choke factors should be chosen so that the processing capacity is fully utilized. When the production reaches a state where this is not possible, the production should be left unchoked. A production strategy satisfying these constraints is said to be admissible. (Huseby & Haavardsson, 2009) developed a general framework for optimizing production strategies with respect to various types of objective functions. The same problem was considered in (Haavardsson et. al., 2008) where a parametric class of production strategies were introduced. (Haavardsson et. al., 2008) also showed how to find an optimal strategy within this class given that all reservoir parameters were known. In the present paper we consider the problem of optimizing the production strategy when the reservoir parameters are uncertain. The uncertainty is represented using the stochastic models introduced in (Haavardsson & Huseby, 2007). In real life reservoir uncertainty typically change over time. Thus, a production strategy considered to be optimal initially may turn out to be far from optimal as more knowledge about the reservoirs is gained. Ideally, one would prefer production strategies which could be updated dynamically as new information is obtained. However, optimizing such dynamic production strategies is a very difficult problem. In the present paper we instead focus on finding production strategies which are robust with respect to variations in the reservoir properties.

Huseby, Arne & Haavardsson, Nils Fridthjov (2009). Multireservoir production optimization. European Journal of Operational Research.
ISSN 03772217.
199(1), s 236 251 . doi:
10.1016/j.ejor.2008.11.023
Show summary
When a large oil or gas field is produced, several reservoirs often share the same processing facility. This facility is typically capable of processing only a limited amount of commodities per unit of time. In order to satisfy these processing limitations, the production needs to be choked, i.e., scaled down by a suitable choke factor. A production strategy is defined as a vector valued function defined for all points of time representing the choke factors applied to reservoirs at any given time. In the present paper we consider the problem of optimizing such production strategies with respect to various types of objective functions. A general framework for handling this problem is developed. A crucial assumption in our approach is that the potential production rate from a reservoir can be expressed as a function of the remaining recoverable volume. The solution to the optimization problem depends on certain key properties, e.g., convexity or concavity, of the objective function and of the potential production rate functions. Using these properties several important special cases can be solved. An admissible production strategy is a strategy where the total processing capacity is fully utilized throughout a plateau phase. This phase lasts until the total potential production rate falls below the processing capacity, and after this all the reservoirs are produced without any choking. Under mild restrictions on the objective function the performance of an admissible strategy is uniquely characterized by the state of the reservoirs at the end of the plateau phase. Thus, finding an optimal admissible production strategy, is essentially equivalent to finding the optimal state at the end of the plateau phase. Given the optimal state a backtracking algorithm can then used to derive an optimal production strategy. We will illustrate this on a specific example.

Haavardsson, Nils Fridthjov & Huseby, Arne (2007). Multisegment production profile models  A tool for enhanced total value chain analysis. Journal of Petroleum Science and Engineering.
ISSN 09204105.
58, s 325 338 . doi:
10.1016/j.petrol.2007.02.003
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Huseby, Arne & Haavardsson, Nils Fridthjov (2009). Multireservoir production optimization under uncertainty.
Show summary
Oil and gas production from several reservoirs are often processed at a single processing facility. Due to limitations in the processing capacity, this implies that the production rates from the individual reservoirs have to be reduced. That is, for each reservoir the production rate is scaled down by a suitable choke factor between zero and one, chosen so that the total production does not exceed the processing capacity. Recent studies of production optimization include (Horne, 2002), (Merabet & Bellah, 2002) and (Neiro & Pinto, 2004). (Huseby & Haavardsson, 2009) introduced the concept of a production strategy, a vector valued function defined for all points of time t ≥ 0 representing the choke factors applied to the reservoirs at time t. As long as the total potential production rate is greater than the processing capacity, the choke factors should be chosen so that the processing capacity is fully utilized. When the production reaches a state where this is not possible, the production should be left unchoked. A production strategy satisfying these constraints is said to be admissible. (Huseby & Haavardsson, 2009) developed a general framework for optimizing production strategies with respect to various types of objective functions. The same problem was considered in (Haavardsson et. al., 2008) where a parametric class of production strategies were introduced. (Haavardsson et. al., 2008) also showed how to find an optimal strategy within this class given that all reservoir parameters were known. In the present paper we consider the problem of optimizing the production strategy when the reservoir parameters are uncertain. The uncertainty is represented using the stochastic models introduced in (Haavardsson & Huseby, 2007). In real life reservoir uncertainty typically change over time. Thus, a production strategy considered to be optimal initially may turn out to be far from optimal as more knowledge about the reservoirs is gained. Ideally, one would prefer production strategies which could be updated dynamically as new information is obtained. However, optimizing such dynamic production strategies is a very difficult problem. In the present paper we instead focus on finding production strategies which are robust with respect to variations in the reservoir properties.

Haavardsson, Nils Fridthjov; Huseby, Arne & Holden, Lars (2008). A Parametric Class Of Production Strategies For MultiReservoir Production Optimization. Statistical research report (Universitetet i Oslo. Matematisk institut. 8.
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When a large oil or gas field is produced, several reservoirs often share the same processing facility. This facility is typically capable of processing only a limited amount of oil, gas and water per unit of time. In the present paper only single phase production, e.g., oil production, is considered. In order to satisfy the processing limitations, the production needs to be choked. That is, for each reservoir the production is scaled down by suitable choke factors between zero and one, chosen so that the total production does not exceed the processing capacity. Huseby & Haavardsson (2008) introduced the concept of a production strategy, a vector valued function defined for all points of time t ≥ 0 representing the choke factors applied to the reservoirs at time t. As long as the total potential production rate is greater than the processing capacity, the choke factors should be chosen so that the processing capacity is fully utilized. When the production reaches a state where this is not possible, the production should be left unchoked. A production strategy satisfying these constraints is said to be admissible. Huseby & Haavardsson (2008) developed a general framework for optimizing production strategies with respect to various types of objective functions. In the present paper we present a parametric class of admissible production strategies. Using the framework of Huseby & Haavardsson (2008) it can be shown that under mild restrictions on the objective function an optimal strategy can be found within this class. The number of parameters needed to span the class is bounded by the number of reservoirs. Thus, an optimal strategy within this class can be found using a standard numerical optimization algorithm. This makes it possible to handle complex, highdimensional cases. Furthermore, uncertainty may be included, enabling robustness and sensitivity analysis.

Haavardsson, Nils Fridthjov; Huseby, Arne; Pedersen, Frank; Lyngroth, Steinar; Xu, Jingzhen & Aasheim, Tore (2008). Hydrocarbon production optimization in fields with different ownership and commercial interests. Statistical research report (Universitetet i Oslo. Matematisk institut. 9.
Show summary
A main field and satellite fields consist of several separate reservoirs with gas cap and/or oil rim. A processing facility on the main field receives and processes the oil, gas and water from all the reservoirs. This facility is typically capable of processing only a limited amount of oil, gas and water per unit of time. In order to satisfy these processing limitations, the production needs to be choked. The available capacity is shared among several field owners with different commercial interests. In this paper we focus on how total oil and gas production from all the fields could be optimized. The satellite field owners negotiate processing capacities on the main field facility. This introduces additional processing capacity constraints (booking constraints) for the owners of the main field. If the total wealth created by all owners represents the economic interests of the community, it is of interest to investigate whether the total wealth may be increased by lifting the booking constraints. If all reservoirs may be produced more optimally by removing the booking constraints, all owners may benefit from this when appropriate commercial arrangements are in place. We will compare two production strategies. The first production strategy optimizes locally, at distinct time intervals. At given intervals the production is prioritized so that the maximum amount of oil is produced. In the second production strategy a fixed weight is assigned to each reservoir. The reservoirs with the highest weights receive the highest priority.

Huseby, Arne & Haavardsson, Nils Fridthjov (2008). A framework for multireservoir production optimization. Statistical research report (Universitetet i Oslo. Matematisk institut. 4.
Show summary
When a large oil or gas field is produced, several reservoirs often share the same processing facility. This facility is typically capable of processing only a limited amount of commodities per unit of time. In order to satisfy these processing limitations, the production needs to be choked, i.e., scaled down by a suitable choke factor. A production strategy is defined as a vector valued function defined for all points of time representing the choke factors applied to reservoirs at any given time. In the present paper we consider the problem of optimizing such production strategies with respect to various types of objective functions. A general framework for handling this problem is developed. A crucial assumption in our approach is that the potential production rate from a reservoir can be expressed as a function of the remaining producible volume. The solution to the optimization problem depends on certain key properties, e.g., convexity or concavity, of the objective function and of the potential production rate functions. Using these properties several important special cases can be solved. An admissible production strategy is a strategy where the total processing capacity is fully utilized throughout a plateau phase. This phase lasts until the total potential production rate falls below the processing capacity, and after this all the reservoirs are produced without any choking. Under mild restrictions on the objective function the performance of an admissible strategy is uniquely characterized by the state of the reservoirs at the end of the plateau phase. Thus, finding an optimal admissible production strategy, is essentially equivalent to finding the optimal state at the end of the plateau phase. Given the optimal state a backtracking algorithm can then used to derive an optimal production strategy. We will demonstrate this on a specific example.

Haavardsson, Nils Fridthjov (2007). Multireservoir production optimization  ensuring an optimal development of large oilfields.

Haavardsson, Nils Fridthjov (2007). Multireservoir production optimization using priority strategies and backtracking methods.

Haavardsson, Nils Fridthjov & Huseby, Arne (2007). The modelling of multisegment production profiles using hybrid systems and ordinary differential equations.

Huseby, Arne & Haavardsson, Nils Fridthjov (2007). Multisegment production profile models, a hybrid system approach. Statistical research report (Universitetet i Oslo. Matematisk institut. 2.
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When an oil or gas field development project is evaluated, having a satisfactory production model is very important. Since the first attempts in the 40's, many different models have been developed for this purpose. Such a model typically incorporates knowledge about the geological properties of the reservoir. When such models are used in a total value chain analysis, however, also economical and strategic factors need to be taken into account. In order to do this, flexible modeling tools are needed. In this paper we demonstrate how this can be done using hybrid system models. In such models the production is modeled by ordinary differential equations representing both the reservoir dynamics as well as strategic control variables. The approach also allows us to break the production model into a sequence of segments. Thus, we can easily represent various discrete events affecting the production in different ways. The modeling framework is very flexible making it possible to obtain realistic approximations to reallife production profiles. At the same time the calculations can be done very efficiently. The framework can be incorporated in a full scale project uncertainty analysis.

Haavardsson, Nils Fridthjov (2006). Segmenterte produksjonsprofilmodeller – et verktøy for forbedret total verdikjedeanalyse.

Haavardsson, Nils Fridthjov (2005). Økonomisk risikoanalyse: en beslutning om utbygging av oljefelt.

Haavardsson, Nils Fridthjov & Haavardsson, Nils F. (2005). A summary of real options methodology.
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Published Jan. 22, 2013 2:53 PM
 Last modified Aug. 25, 2014 2:05 PM