How do you monitor well performance and reservoir behavior with log data?

1 Basic concepts of well logging

Well logging is the process of recording and interpreting measurements of various physical phenomena along the wellbore. These measurements are obtained by lowering specialized tools or sensors into the well, either during or after drilling, or by using permanent sensors installed in the well casing. The tools or sensors can emit or detect signals such as electrical currents, acoustic waves, electromagnetic waves, nuclear radiation, or mechanical forces, and measure their responses from the surrounding rock and fluid layers. The recorded data are then displayed as curves or images on a log, which can be analyzed to infer the properties and conditions of the subsurface.

2 Types of log data

There are many types of log data that can be used to monitor well performance and reservoir behavior, depending on the objectives and challenges of each project. Spontaneous potential (SP) and resistivity logs measure the natural and induced electrical potentials and resistances in the wellbore and the formation, respectively, helping to identify boundaries, thicknesses, porosity, water saturation, and hydrocarbon content. Gamma ray and neutron logs measure radiation from the formation, which depends on mineral composition and fluid content, allowing for distinction between sandstone, shale, limestone, and dolomite formations as well as porosity and fluid saturation estimation. Sonic and acoustic logs measure the travel time and amplitude of sound waves in the wellbore and formation that depend on density, elasticity, and fluid content; they can help determine rock mechanical properties such as Young's modulus, Poisson's ratio, and compressive strength while detecting fractures, faults, or fluid movements. Density and caliper logs measure bulk density and diameter of the wellbore and formation that depend on rock density, porosity, shape; they can help calculate formation volume factor, compressibility, net pay thickness of the reservoir as well as identify borehole problems. Pressure and temperature logs measure static/dynamic pressure/temperature in wellbore/formation that depend on fluid density/viscosity/compressibility/flow rate; they can help evaluate reservoir pressure/fluid gradient/productivity index/skin factor of the well as well as detect any pressure or temperature anomalies or barriers.

3 Interpretation methods of log data

Interpreting log data involves applying various methods and models to convert the raw measurements into meaningful parameters and indicators of well performance and reservoir behavior. Crossplotting is a common method which plots two or more log data sets against each other to identify trends, correlations, or outliers. Petrophysical modeling uses mathematical equations or empirical relationships to relate the log data to the physical properties of the rock and fluid. Inversion uses numerical algorithms or optimization techniques to reconstruct the subsurface structure or properties from the log data. Integration combines different types of log data or other sources of information, such as core samples, seismic data, or production data, to improve the accuracy and reliability of the interpretation. All of these methods are important for accurately understanding well performance and reservoir behavior.

4 Applications of log data

The applications of log data for monitoring well performance and reservoir behavior are numerous and varied, depending on the goals and challenges of each project. For example, log data can be used to characterize the reservoir quality, such as porosity, permeability, net pay, hydrocarbon saturation, and fluid type. Additionally, it can be used to design and optimize well completion and stimulation operations, such as casing, cementing, perforating, fracturing, or acidizing. Furthermore, log data can be used to conduct and analyze well tests to estimate reservoir parameters and monitor production problems. Finally, it can be used to update and calibrate reservoir models to forecast and optimize the reservoir performance.

5 Challenges and opportunities of log data

The use of log data for monitoring well performance and reservoir behavior presents various challenges and opportunities. Quality and uncertainty of log data is highly dependent on the tool design, calibration, operation, and maintenance, as well as borehole and formation conditions. To ensure reliability and accuracy of log data, proper quality control, correction, and validation procedures must be applied. Integrating and analyzing log data requires advanced skills and tools, such as data management, visualization, processing, modeling, and interpretation software. Investing in training, innovation, and knowledge sharing is essential to enhance the value and efficiency of log data. Additionally, the acquisition and transmission of log data involves various challenges regarding cost, time, safety, environmental impact, availability, accessibility, and security. Exploring new technologies and methods such as logging while drilling or wireless communication can improve the performance and sustainability of log data.

6 Here’s what else to consider

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