# Reservoir Performance Prediction in Steam Huff and Puff Injection Using Proxy Modelling
## 1 Introduction
It can provide results instantly, compared to the whole process of reservoir simulation, which incorporates screening, modeling, history matching, field development planning, and running the simulation. In reservoir engineering, proxy modeling has mainly been used for sensitivity analysis, risk analysis, history matching, production forecasting, and production optimization [17; 18; 19; 20; 21]. Prediction of reservoir performance is considered one of the main proxy model applications. Numerous proxy models for different reservoirs under different production methods have been developed and reported in the literature. For instance, [PERSON] et al. [22] developed a proxy model to optimize cumulative oil production for the steam-assisted gravity drainage method. [PERSON] [23] built a proxy model using a fuzzy pattern algorithm to mimic a giant oil field simulation, where the proxy model outcomes are oil and water production over time. Artificial neural network (ANN) proxy models were developed by [PERSON] et al. [24] for the CO\({}_{2}\) and N\({}_{2}\) cyclic injection method to predict oil production; by [PERSON] and [PERSON] [25] to predict coalbed methane production; by [PERSON] et al. [26] to predict fluid production in gas condensate reservoir; by [PERSON] and [PERSON] [27] in a polymer flooding process; and by [PERSON] et al. [28] to forecast well production in a tight oil reservoir. [PERSON] and [PERSON] [29] constructed a proxy model to predict cumulative production from a fractured shale gas reservoir. [PERSON] and [PERSON] [30] built a proxy model to predict optimum oil recovery for an immiscible gas-assisted gravity drainage method. [PERSON] et al. [31] generated proxy models based on response surface methodology to predict fluid production, Net Present Value (NPV), and the recovery factor of oil. [PERSON] et al. [32] applied the same algorithm, comparing it to the least square support vector machine algorithm to predict hydrocarbon production from shales. Box-Behnken design was used to develop a statistical proxy model by [PERSON] et al. [33] to estimate incremental oil recovery under a CO\({}_{2}\)-water alternating gas (WAG) scheme and [PERSON] et al. [34] to predict oil recovery in miscible CO\({}_{2}\) injection. Proxy models that predict reservoir performance for steam huff and puff injection are rarely found. Attempts to develop universal proxy models for the specified case were instigated by [PERSON] [35], [PERSON] and [PERSON] [36], and [PERSON] and [PERSON] [37]. The models were presented as general models and some are the continuation and improvements from previous works over the years. [PERSON] [35] developed an expert system consisting of ANN proxy models for steam huff and puff injection with horizontal wells in a naturally fractured reservoir. The inputs of the model are reservoir rock and fluid properties, operation design parameters, and fracture design parameters. The forward models predict outputs such as the number of cycles, cycle duration, oil flowrate, and cumulative oil production. Inverse models were developed to predict operation parameters and fracture design parameters, using performance indicators such as oil production and production period as additional inputs. Most of the reservoir parameters were assumed constant, such as oil density, relative permeability, anisotropy, and capillary pressures. It was reported that the majority of testing cases had a difference in the number of cycles by two cycles, but the production prediction still falls within the acceptable error margin. [PERSON] and [PERSON] [36] developed ANN proxy models for steam huff and puff injection. The study had the same workflow where forward and inverse models were generated as an expert system. In addition, two case studies describing examples of potential practical applications were presented. The first case study compared the performance of proxy models to the reservoir simulation result using the same inputs.