Title

Novel Mathematical Models to Predict Preformed Particle Gel Placement and Propagation through Fractures

Abstract

Preformed particle gel (PPG) treatments have been widely used in the industry in order to improve conformance by overcoming reservoir heterogeneity. In this study, several correlations have been generated and validated experimentally in order to model millimeter gel particles', also referred to as PPG, propagation and placement in fractures, open hole plates, and void spaces. Three Experimental setups were used in order to study the factors affecting gel propagation in fractures, channels modeled by open hole plates, and void spaces modeled using tubes. The setups were used in order to study the effect of flow rate, fracture width, and gel strength on the resistance factor, and the gel injection pressure gradient. From the results, the data analysis was conducted using statistical tools to deduce if the three experimental models where consistent, and if so, generate three mathematical models, Resistance Factor versus the Shear Rate, Pressure Gradient vs Flow rate, and, Pressure Gradient versus Fracture Width. A validation of each correlation was performed using data not used in the generation of the correlations. A high accuracy fit was obtained during the validation of each of the correlations. The gel strength was included in all the newly developed models since it affects the gel propagation. This makes them a significant tool in order to accurately predict the pressure gradient of the PPG while it is being injected by simply knowing the particles' gel strength, the flow rate used to inject the particles, and the fracture width. Pressure gradients, obtained using this correlation, were also plotted with pressure gradients obtained from in-situ gel injection. The correlation predicted higher pressure gradients than those of the in-situ gel, which is true since the particles are solids, whereas the in-situ gel is injected as a fluid. The resistance factor model was also used to validate a previously generated model that was used in the UTGEL Simulator. Based on the validation of all the newly developed mathematical models, they can be used to predict the gel particles' injection and propagation through fractures, channels, and void spaces with high accuracy. This is a large addition in terms of PPG treatment since no previous models could accurately predict the gel placement and propagation in these reservoir features. By proving the accuracy of the models using the lab results these correlations can save largely on time by directly predicting the gel injection pressure gradient and resistance factors, rather than having to perform extensive lab experiments. Also, the correlations can help in properly performing a PPG treatment, while avoiding complications such as pump failure and formation fracturing.

Meeting Name

SPE Annual Technical Conference and Exhibition 2017 (2017: Oct. 9-11, San Antonio, TX)

Department(s)

Geosciences and Geological and Petroleum Engineering

Comments

Funding for this project was provided by DOE under contract of DE-FE0024558 and the Joint Industry Project Members of Missouri S&T Particle Gel Conformance Control Consortium including Conoco-Philips, Occidental and Daqing New Wantong Oilfield Chemical Co.

Keywords and Phrases

Forecasting; Fracture; Petroleum engineering; Petroleum reservoir evaluation; Shear flow; Statistical mechanics, Developed model; Experimental models; Fracture width; Gel placement; Injection pressures; Reservoir heterogeneity; Resistance factors; Statistical tools, Pressure gradient

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2017 Society of Petroleum Engineers (SPE), All rights reserved.

Publication Date

01 Oct 2017

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