Stochastic Modeling Technique for Heterogeneous Multi-layer Sandstone Reservoir

Abstract

According to the characteristic of the heterogeneous multi-layer continental sandstone reservoir in Daqing Oil Field, this paper studies a set of stochastic modeling techniques. Multi-step modeling possesses a sound geologic base for predicting various reservoir parameters by microfacies controlling. In order to make a better use of variogram, a single layer is used as modeling unit, resulting in a detailed and reliable model. The depositional microfacies distribution model is improved by man-computer interaction, with detailed consideration of geologists' experiences. Different modeling methods suitable for various types of sandbodies are discussed, and interpretation technique of logging parameters combining petrophysical facies with artificial neural network is developed. The modeling results from unit PII10 in the middle of the northern Block I of Daqing oilfield proves the adaptability of this technique, which provides a new means for identification of the reservoir heterogeneity and uncertainty of understanding. Introduction The Sa-Put-Gao Reservoir in Daqing oilfield is a typical continental multi-layer sandstone reservoir with rapid change of depositional facies in area, and great different properties in various microfacies. Different depositional facies alternate in vertical, result in complex heterogeneity of the reservoir. Over 40 years' development, the oilfield has entered into the later period of high water cut. The heterogeneity of the reservoir is the main cause influencing the recovery. The geologic study of oilfield development is a process of continuous study on the heterogeneity. Reservoir characterization meets with more challenges for improving economic and effective recovery in the later period of oil field development. In recent years, the technique of stochastic modeling is widely used in reservoir characterization, providing a new method for identifying the uncertainty of reservoir characterization with different scales and data resources. According to the depositional characteristics of heterogeneous multi-layer sandstone reservoirs, this paper discusses a method of stochastic predicting modeling based on the logging data of dense wells patterns guided by relative knowledge of sedimentology. Aiming at establishing detailed geologic model of heterogeneous multi-layer sandstone reservoirs, a set of stochastic modeling technique is summarized in this paper, and stochastic models in studied area are constructed. The Depositional Characteristics and Current Data Available of the Heterogeneous Sandstone Reservoirs in Daqing Oilfield Sa-Pu-Gao Reservoir in Daqing Oilfield is a large shallow-water lake basin fluvial-deltic deposit formed in the middle to late period of early Cretaceous. During deposition, the lake basin is very shallow and gentle. Affected by the factors such as tectonic movement, climate change and source supply, alternating layers of sand and shale were formed characterized by a wide distribution deposit, various depositional types, multiple layers, thin single layer, and a large thickness of the whole formation. It has following characteristics. 1. The reservoir distributes vertically with long intervals, multiple layers, and thin single layer. The oil-bearing interval Sae-Put-Gao Reservoir in the north part of Daqing oilfield is 300~500m with more than 100 layers penetrated, and 120~150 single sand layers can be further divided with a thickness of 1~3m. The thinnest layer is only 0.2–0.4m, and the thick distributary channel sandbody is 3~6m. Only a few stacked channels are 10m thick.

A mathematical model and semi-analytical solution for transient pressure of vertical fracture with varying conductivity in three crossflow rectangular layers

“…The methods and equations for calculating transient pressure with wellbore storage and skin effects of a non-fractured well in crossflow/no-crossflow multilayered reservoir were presented (Bourdet, 1985; Kucuk et al., 1986; Lefkovits et al., 1961; Liu and Wang, 1999; Tariq and Ramey, 1978). The transient pressure of a multilayered reservoir and the difference of interlayer communication were performed and analyzed by many researchers (Aly, 1994; Aly and Lee, 1995; Bello et al., 2016; Eisa et al., 2008; Frantz et al., 1992; Gao, 1986; Jatmiko et al., 1996; Jordan and Mattar, 2000; Lu et al., 2000; Nikjoo and Hashemi, 2012; Ryan et al., 1994; Sun et al., 2003; Wang and Wang, 2014a, 2014b; Valdes-Perez et al., 2018; Yuan et al., 2016; Zhang et al., 2001).…”