Interpretation of Temperature Data during Acidizing Treatment of Horizontal Wells for Stimulation Optimization

Abstract

Abstract Optimum fluid placement is crucial for successful acid stimulation treatments of long horizontal wells where there is a broad variation of reservoir properties along the wellbore. Various methods have been developed and applied in the field to determine the fluid placement and effectiveness of the diversion process, but determining the injection profile during the course of matrix acidizing still remains a challenge. Recently, distributed temperature sensing technology (DTS) has enabled us to observe the dynamic temperature profile along the wellbore during acid treatments. Quantitative interpretation of dynamic temperature data can provide an invaluable tool to assess the effectiveness of the treatment as well as optimize the treatment through on-the-fly modification of the treatment parameters such as volume, injection rate and diversion method. In this paper we discuss how fluid placement can be quantified using dynamic temperature data. A mathematical model has been developed to simulate the temperature behavior along the wellbore during and shortly after acid treatments. This model couples a wellbore and a near-wellbore flow and thermal model considering the effect of both mass and heat transfer between the wellbore and the formation. The model accounts for all significant thermal processes involved during a treatment, including heat of reaction, conduction, convection. Then, an inversion procedure is applied to interpret the acid distribution profile from the measure temperature profiles. To illustrate how to apply the model and analyze the DTS data, examples of matrix acidizing are presented. The temperature, flow and pressure data were generated by a horizontal well acidizing simulator. The inverse model is verified and also the effect of the distribution of stimulation fluid along the lateral and the effectiveness of the diversion processes on the transient temperature response is discussed. We address some issues regarding solving the inverse problem and discuss the alternative methods of using warm-back information for cases in which inversion is difficult. Introduction Matrix acidizing is a common stimulation technique applied to remove near-wellbore formation damage and increase the natural permeability in both vertical and horizontal wells. It involves injecting acid solutions, usually hydrofluoric (HF) and/or hydrochloric (HCl) acids, into the formation to restore the original reservoir permeability through chemical reactions. In the matrix acidizing treatment, optimum fluid placement and damage removal is crucial for success, both for long horizontal wells where there is a broad variation of reservoir properties along the wellbore, and for vertical wells with multiple zones and/or extensive productive intervals. It is difficult to evaluate the placement of the stimulation fluid and damage removal in real-time during the course of the matrix acidizing of a horizontal well or a vertical well with multiple zones. Pre-job matrix acidizing simulators can provide a theoretical prediction of the acid injection distribution and damage removal with prediction performance based on the limited information about the formation properties that is going to be treated. However, during the stimulation treatments unpredictable downhole conditions can have significant impact on the results. When treatment is completed, production logging tools and radioactive tracers sometimes are used to provide some valuable feedback about the effectiveness of the treatment. However, well intervention during the treatment is required to obtain this data. Also, the data is not available until the treatment is finished, which does not allow for real-time treatment monitoring and optimization.