A Tool to Manage Water Production in a Naturally Fractured Reservoir Using Flowing Pressure Data and Water Level Measurement

Abstract

A key reservoir management guideline for a water driven, naturally fractured reservoirs is to minimize water production. Water breakthrough is undesirable as it drastically reduces oil production rate because of unfavorable mobility ratio and lower oil recovery due to poor sweep efficiency. This paper details a new analytical tool developed in DNO to (i) monitor water flooding, (ii) predict water breakthrough and (iii) mitigate post-breakthrough flooding, aiming to maximize dry oil production and to prevent fast escalation of water cut. The tool is based entirely on field measured parameters such as fluid properties, bottom hole pressures (DHG) and gradiometric surveys. A proper reservoir management workflow includes a systematic and continual monitoring of water level depths in all, or some key wells, completed in the reservoir. To achieve such a goal, analytical well-specific models were developed. Full field models have serious limitations to handle the well scale, and coning critical rate correlations available in the literature are very simplistic. Well models are, on the other hand, well-specific, based exclusively on (i) bottom hole flowing pressure data, being collected on a quasi-real-time basis with pressure downhole gauges, and (ii) periodic water level depths measured in observation wells with gradiometric surveys, and (iii) fluid properties. First principles are applied to articulate the data and no assumption is made related to neither flow path geometry nor permeabilities. Well model, known as Water Towers model, are used primarily to track water level depths in each well and to predict and manage water breakthrough time. They have proved to be effective in fracture networks that are controlled by gravity. The Water Towers consists of a set of simple equations that relate the variables listed above with the vertical velocity of water. They make use of measured water level depths to calibrate the dimensions of the well vertical column and to adjust the calculations for the convoluted effect of tortuosity of the flow path followed by water, local pressure decline, inflow from tributary fractures, and well interference. In addition to their primary use, they are effective to decide on the optimal rate of the wells and to investigate the existence of alternative water sources (different from the underlying aquifer). The Water Towers model is part of the toolbox developed by DNO to manage some of the assets it operates. It has been successful in forecasting water breakthrough in vertical and horizontal wells, in estimating the advance depth of water level in wellbores and in providing guidelines concerning the optimum rate of wells. The reliability relies on the fact that their input is exclusively measured data. The more extensive the data set is, the more reliable the results are. These models are a relevant and reliable tool in proactive managing of naturally fractured reservoirs driven by an underlying aquifer and are of interest to those engaged in optimizing the production of this kind of reservoirs.