(399b) Design of Optimal Multi-Size Proppant Pumping Schedule to Enhance Shale Gas Production

Hydraulic fracturing is a technique extensively used in the oil and gas industry, where water, proppant (sand) and additives are injected into unconventional reservoirs to enhance the recovery of shale hydrocarbon. Although some previous studies have developed pumping schedules that maximize gas production for a single-size proppant [1, 2], they did not consider the effect of varying proppant diameters across pumping stages on shale gas production. For determining the oil and gas production from unconventional reservoirs, average propped surface area (PSA) and average fracture conductivity (FC) of the propped hydraulic fractures play an important role, all of which depend largely on the injected proppant diameter. Unfortunately, existing studies on average PSA or average FC considered these two effects separately, and did not consider their combined effect on shale gas production [3, 4].

Motivated by this lack of fundamental studies on this important topic, we first conducted a sensitivity analysis to study the effect of multi-size proppant during hydraulic fracturing on shale gas production from unconventional reservoirs. From the sensitivity analysis, we found out that the pumping schedule used for hydraulic fracturing determines the average PSA and average FC of the propped fractures, which in-turn are two useful parameters that determine the cumulative shale gas production volume from an unconventional reservoir. Therefore, we developed a framework called Sequentially Interlinked Modeling Structure (SIMS) to predict the average PSA, average FC and cumulative shale gas production volume for a given pumping schedule. The first model in SIMS is a multivariable output error state space (MOESP)-based reduced-order model (ROM) of the fracturing process, which provides the pre-shut-in average PSA and pre-shut-in average FC as the outputs. The second model in SIMS is an artificial neural network (ANN) that has been used to accurately simulate the gravity-induced proppant settling process, which provides the post-shut-in average PSA and post-shut-in average FC as the outputs. The third model in SIMS is a map that links the average PSA and the average FC of the created hydraulic fractures to the cumulative shale gas production volume from an unconventional reservoir. These models are interlinked in the sense that the output from the first model is the input to the second, and the output from the second model is the input to the third. Since this approach also provides us with average PSA and average FC values in the intermediate step after the hydraulic fracturing operation that typically takes a few hours, these parameters are usually more important to the oil and gas industries instead of just the cumulative shale gas production volume at the end of 10 years. Then, we used the SIMS framework to obtain a multi-size proppant pumping schedule that maximizes shale gas production. Finally, we demonstrated that obtained pumping schedule gives a gas production volume greater than the values obtained from the existing pumping schedules which consider only single-size proppant.

References:

[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, 1638-1650.

[2] Siddhamshetty, P., Bhandakkar, P., & Kwon, J.S. (2020). Enhancing total fracture surface area in naturally fractured unconventional reservoirs via model predictive control. Journal of Petroleum Science and Engineering, 184, 106525.

[3] Wahl, H.A. (1965). Horizontal fracture design based on propped fracture area. Journal of Petroleum Technology, 17, 723 – 730.

[4] Ramurthy, M., Barree, R.D., Kundert, D.P., Petre, J.E., Mullen, M.J. (2011). Surface-area vs. conductivity-type fracture treatments in shale reservoirs. In SPE Hydraulic Fracturing Technology Conference, The Woodlands, TX.