(371ak) Enhancing Total Fracture Surface Area in Naturally Fractured Unconventional Reservoirs Via Model Predictive Control

Siddhamshetty, P., Texas A&M Energy Institute, Texas A&M University
Bhandakkar, P., Texas A&M Energy Institute
Kwon, J., Texas A&M University
In hydraulic fracturing, it is important to create fractures with a desired geometry to maximize the oil and gas extraction from unconventional reservoirs. Recently, several efforts have been made to achieve the desired fracture geometry by developing real-time feedback control systems to compute fracturing fluid pumping schedule (e.g., fracturing fluid injection rate and proppant concentration at the wellbore) for hydraulic fracturing [1, 2]. However, they did not consider natural fractures, which may result in a complex fracture geometry [3]. Because of complex fracture growth, the ultimate goal of hydraulic fracturing in naturally fractured unconventional reservoirs should be changed from achieving a desired fracture geometry to maximizing the total fracture surface area for given fracturing resources as it will allow more drainage area available for oil and gas recovery. Therefore, the pumping schedule computed using previous control schemes cannot be directly applied to naturally fractured unconventional reservoirs.

The main objective of this study is to develop a model-based pumping schedule by utilizing a recently developed unconventional complex fracture propagation model called Mangrove describing complex fracture networks by accounting for interaction between the hydraulic fractures and natural fractures [4, 5]. One of the challenges is that Mangrove does not report the values of stimulated reservoir volume (SRV), and it is important to predict the SRV as it is the only available real-time measurement during the hydraulic fracturing process using microseismic monitoring technique. Therefore, we developed a new subroutine in Mangrove to calculate the SRV. Then, we constructed a surrogate model that describes the relationship between the manipulated input variables (i.e., fracturing fluid injection rate and proppant concentration at the wellbore) and output variables (SRV and total fracture surface area) using the data generated from the Mangrove with the proposed subroutine. Next, we designed a Kalman filter utilizing the measurement of SRV to estimate the total fracture surface area. Then, a model-based feedback control system is proposed to determine the fracturing fluid pumping schedule that maximizes the total fracture surface area. The closed-loop simulation results demonstrate that the obtained total fracture surface area can lead to enhanced oil and gas production rates from naturally fractured unconventional reservoirs.


[1] Siddhamshetty, P., Kwon, J.S., Liu, S., & Valkó, P.P. (2017). Feedback control of proppant bank heights during hydraulic fracturing for enhanced productivity in shale formations. AIChE Journal, 64(05), 1638-1650.

[2] Siddhamshetty, P., Yang, S., & Kwon, J.S. (2018). Modeling of hydraulic fracturing and designing of online pumping schedules to achieve uniform proppant concentration in conventional oil reservoirs. Computers & Chemical Engineering, 114, 306-317.

[3] Gale, J.F., Laubach, S.E., Olson, J.E., Eichhubl, P., & Fall, A. (2014). Natural fractures in shale: A review and new observations. AAPG bulletin, 98(11), 2165-2216.

[4] Weng, X., Kresse, O., Chuprakov, D., Cohen, C.E., Prioul, R., & Ganguly, U. (2014). Applying complex fracture model and integrated workflow in unconventional reservoirs. Journal of Petroleum Science and Engineering, 124, 468-483.

[5] Weng, X., Kresse, O., Cohen, C.E., Wu, R., & Gu, H. (2011, January). Modeling of hydraulic fracture network propagation in a naturally fractured formation. In SPE Hydraulic Fracturing Technology Conference. Society of Petroleum Engineers.