Abstract

Summary Building an integrated subsurface model is one of the main goals of major oil and gas operators to guide the field-development plans. All field-data acquisitions from seismic, well logging, production, and geomechanical monitoring to enhanced-oil-recovery (EOR) operations can be affected by the accurate details incorporated in the subsurface model. Therefore, building a realistic integrated subsurface model of the field and associated operations is essential for a successful implementation of such projects. Furthermore, using a more reliable model can, in turn, provide the basis in the decision-making process for control and remediation of formation damage. One of the key identifiers of the subsurface model is accurately predicting the hydraulic-flow units (HFUs). There are several models currently used in the prediction of these units on the basis of the type of data available. The predictions that used these models differ significantly because of the assumptions made in the derivations. Most of these assumptions do not adequately reflect realistic subsurface conditions, thus increasing the need for better models. A new approach has been developed in this study for predicting the petrophysical properties and improving the reservoir characterization. The Poiseuille flow equation and Darcy equation were coupled, taking into consideration the irreducible water saturation in the pore network. The porous medium was introduced as a domain containing a bundle of tortuous capillary tubes with irreducible water lining the pore wall. A series of routine and special core analysis was performed on 17 Berea sandstone samples, and the petrophysical properties were measured and X-ray diffraction (XRD) analysis was conducted. In building the petrophysical model, it was initially necessary to assume an ideal reservoir with 17 different layers, each layer representing one Berea sample. Afterward, by the iteration and calibration of the laboratory data, the number of HFUs was determined by use of the common HFU model and the proposed model accordingly. A comparative study shows that the new model provides a better distribution of HFUs and prediction of the petrophysical properties. The new model provides a better match with the experimental data collected than the models currently used in the prediction of such parameters. The good agreement observed for the Berea sandstone experimental data and the model predictions by use of the new permeability model shows a wider range of applicability for various reservoir conditions. In addition, the model has been applied to a series of core-analysis data on low-permeability Medina sandstone, Appalachian basin, northwest Pennsylvania. The flow-unit distribution by use of the proposed model shows a better flow-zone distinction, and the permeability/ porosity relationship has a higher confidence coefficient.

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