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ABSTRACT: Unconventional resources have become the core business of many petroleum companies to meet the increasing demand for energy. Several technologies and methods have been developed and deployed to unlock the potential of tight and ultra-tight formations. Hassi Tarfa (HTF) oil field is a thin and tight sandstone reservoir in Algeria, with an average permeability of less than 0.5 mD. However, all drilled wells in this field are vertical. Hydraulic Fracturing (HF) is the prime stimulation technique that is applied to increase oil recovery in unconventional reservoirs. Although the well production tremendously increases after fracking operation, it does not sustain for longer period of time, which keeps the estimated ultimate recovery (EUR) to be relatively low. In this study, a reservoir model was built and history matched, in order to consider three scenarios to optimize the horizontal lateral length in the HTF field. Then, multistage HF design was simulated using advanced 3D finite element software and exported to the model to estimate the potential increase of EUR. Sensitivities on number of HF stages, fluid volumes, and proppant were conducted to identify the optimal number of HF stages. The results of this study showed that, employing multistage hydraulic fracturing along horizontal drilling can significantly improve the oil recovery in HTF formation. Fracture length and the number of stages showed to be important design parameters. This study also identified the optimal range of operational parameters such as pumping schedule, proppant mass and perforation interval which are crucial to the cost reduction and operation efficiency.
1. INTRODUCTION Global energy demand has increased considerably in the last decades due to the increase of the world population, manufacturing activities, and the high living standards, which calls for efficient energy recovery methods. Oil recovery factor from primary depletion for shale and tight formation has been predicted typically to be less than 10% (Alvarez et al, 2016). To overcome the resistance of the low to extremely low permeability to hydrocarbons flow from reservoir to bottom-hole, the petroleum industry has started implementing several enhanced oil recovery (EOR) mechanisms and technologies (Chemmakh et al., 2021; Ozotta et al., 2021). The combination of horizontal well drilling and multi-stage fracturing, and completion technologies has been the key, over the last two decades, to economically unlock the potential of unconventional reservoirs (Shengnan and Wang, 2012; Kegang et al, 2016). The horizontal section drilled maximizes exposure to the reservoir, while multi-stage fractures increase drainage area and build an effective connection between reservoir and horizontal wellbore. Cost effective Hydraulic Fracturing (HF) design is crucial to mobilize oil in tight formation. An integrated approach is essential to optimize fracture parameters using a reliable geomechanical model and reliable reservoir simulations to predict the post-fracture productivity (Rahman et al, 2014). The industry experience has showed that one third of the fractured clusters contribute with up to 75% of production. Far et al. (2015) observed that resulting production is lithology dependent and some specific variables correlate well with reservoir fracturability and production. The approach developed maximizes the use of well logs and cuttings analysis to determine where to place the frac stage and perforation clusters. Several studies had investigated the optimum horizontal length to maximize recovery. In the Bakken formation in the Williston Basin, USA for instance, the horizontal lateral length typically exceeds 10,000 ft with more than 30 HF stages. It is substantiated in literature that the various in lithology and geology lead to different optimal stage intervals, therefore different ultimate oil recovery. Wang et al. (2019) proposed an innovative approach to optimize horizontal well fracturing with great success. A set of seismic methods were implemented to accurately visualize the formation around the wellbore, select the best azimuth, frac location and direction. Recently, artificial intelligence has been widely implemented in the petroleum industry. Andrei and Connel (2019) applied fuzzy logic to build a data driven model, which was used to identify reservoir quality and eventually horizontal well placement. Likewise, Elkin et al. (2018) employed Monte Carlo technique to optimize horizontal well length. Al Shueili et al. (2022) presented the lessons learned about how to approach horizontal well multistage fracturing program in tight multi-layered and laminated reservoir. Based on the production model, they reported that four to five HF stages for 1000 m lateral length is sufficient to connect the required layers.
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