Applications of 3D Streamline Simulation to Assist History Matching

Abstract

The use of 3D streamline methodologies as an alternative to finite difference simulation has become more common in the oil industry. When the assumptions for its application are satisfied, results from streamline simulation compare excellently with those from finite difference and typically require less than 10% of the CPU resources. The speed of 3D streamline simulation lends itself not just to simulation but also to other components of the reservoir simulation work process. This is particularly true of history matching. History matching is frequently the most tedious and time-consuming part of a reservoir simulation study. In a previous paper (SPE# 49000), we described a novel method that uses 3D streamline paths to assist in history matching finite difference models. We designated this technique Assisted History Matching (AHM) to distinguish it from automated history matching techniques. In this manuscript, we describe this technique in more detail through its application in three reservoir simulation studies. The example models range in size from 105 to 106 grid blocks and contain several dozen to several hundred wells. These applications have led to refinements of the AHM methodology, the incorporation of several new algorithms, and some insights into the processes typically employed in history matching. Introduction The advent of powerful geostatistical modeling techniques have led to the development of very large >107 cells) geocellular reservoir models. These models capture, in greater detail then before, the heterogeneity in porosity, permeability, lithology, etc. that are critical to accurate simulation of reservoir performance. 3D streamline simulation (3DSM) has received considerable attention over the past several years because of its potential as an alternative to traditional methods for the simulation of these very large models. While 3DSM is a powerful simulation tool, it also has a number of other uses. The speed of 3D streamline simulation is ideal for such applications as geologic/geostatistical model screening1, reservoir scoping and, the focus of this paper, history matching. In a previous paper2, we described a methodology to use 3D streamline information to aid in the process of history matching. In this manuscript, we briefly review that technique and present three example reservoir applications that demonstrate its utility. Assisted History Matching The models that are used in reservoir simulation today contain details of structure and heterogeneity that are orders of magnitude greater than that used just 10 years ago. However, there is still (and probably will always be) a large degree of uncertainty in the property descriptions. Geologic data is typically scattered and imprecise. Laboratory measurements of core properties, for example, often show an order of magnitude variation in permeability for any given porosity and several orders of magnitude variation over the data set. It is unlikely that any geologic model will perfectly match the observed reservoir performance without adjustments. History matching will continue to be the technique by which the adjustments are made to the geologic model in order to achieve a match between model and historical reservoir performance. Assisted History Matching The models that are used in reservoir simulation today contain details of structure and heterogeneity that are orders of magnitude greater than that used just 10 years ago. However, there is still (and probably will always be) a large degree of uncertainty in the property descriptions. Geologic data is typically scattered and imprecise. Laboratory measurements of core properties, for example, often show an order of magnitude variation in permeability for any given porosity and several orders of magnitude variation over the data set. It is unlikely that any geologic model will perfectly match the observed reservoir performance without adjustments. History matching will continue to be the technique by which the adjustments are made to the geologic model in order to achieve a match between model and historical reservoir performance.

Recent progress on reservoir history matching: a review

“…They did not impose prior constraints or variogram information, but they did point out some limitations to the streamline method, including no changes to the streamlines and no new wells. Milliken et al [117] used 3D streamline paths to assist manual history matching of three reservoir simulation studies. The example models range in size from 10 5 to 10 6 gridblocks and contain as many as several hundred wells.…”

Consideration Factors in Defining an Effective Scale Management Strategy During Early Stages of Field Development Planning

“…Streamline simulation uses an alternative computational technique (in comparison to finite difference simulation) to modeling fluid flow in hydrocarbon reservoirs (Milliken et al 2000). It is an implicit pressure-explicit saturation (IMPES) method of simulation in which pressure is solved implicitly over the whole grid.…”

Streamline Technology: Reservoir History Matching and Forecasting = Its Success, Limitations, and Future

“…This allows engineers to perform a one-step process that evaluates both vertical and areal sweep, and also accounts for well changes. There has been an explosion of studies that have highlighted the usefulness of streamlines (12)(13)(14)(15)(16)(17)(18)(19) . In many field situations gravity and vertical heterogeneity are important parameters for waterflood recovery.…”