Distributed Temperature Sensing for Wellbore Flow Distribution
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Solution Overview
Problem
Current methods for determining flow distribution in wellbores during stimulation treatments are largely qualitative and ineffective, especially in wells with non-uniform rock properties, leading to inefficient fluid distribution and potential errors in interpreting temperature changes caused by reactive fluids.
Innovation Solution
A method involving Distributed Temperature Sensing (DTS) technology, where a sensor measures temperature and pressure changes over time, generating simulated and actual models to compare and adjust parameters for accurate flow distribution analysis, allowing for real-time adjustments during stimulation treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional flow measurement through production logging is used, then the measurement is valid as long as flow distribution does not change, but it cannot provide instantaneous measurement when flow distribution changes quickly during stimulation treatment
Solution Approach 1:
The patent replaces traditional mechanical flow meters with Distributed Temperature Sensing (DTS) technology using optical fibers. The DTS system measures temperature changes along the wellbore to infer flow distribution, providing continuous real-time monitoring without the mechanical constraints and response delays of traditional flow meters.
Solution Approach 2:
The patent uses temperature as an intermediary parameter to indirectly measure flow distribution. Instead of directly measuring flow with a flow meter, the system measures temperature changes in the wellbore fluid, which correlate with flow rates, providing continuous monitoring capability during stimulation treatments.
2Measurement precision
If DTS technology is used to measure temperature changes for flow distribution, then instantaneous measurement is achieved, but qualitative interpretation errors occur due to reactive fluids affecting temperature changes
Solution Approach 1:
The patent implements a feedback mechanism where the DTS temperature measurements are continuously compared against predictions from a numerical model of the stimulation treatment. This feedback loop allows the system to distinguish between temperature changes caused by fluid flow and those caused by reactive fluid-formation interactions, improving the reliability of flow distribution interpretation.
Solution Approach 2:
The patent uses numerical modeling to predict expected temperature changes from the stimulation treatment before analyzing the actual DTS data. By having these predictions available in advance, the system can compare them against measured temperatures and isolate the flow-related temperature signals from those caused by chemical reactions or other treatment effects.
3Manufacturing precision
If coiled tubing is used to direct fluid to specific layers, then precise fluid placement is achieved, but the operator must know which layers need treatment beforehand
Solution Approach 1:
The patent enables the treatment system to self-adjust based on real-time DTS measurements of flow distribution. The system continuously monitors which layers are receiving fluid and automatically directs the coiled tubing to redirect fluid to under-treated layers, eliminating the need for prior knowledge of formation properties and enabling adaptive treatment optimization.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides a quantitative assessment of flow distribution, enabling more effective stimulation by optimizing fluid placement and reducing errors in interpreting temperature changes, thereby enhancing hydrocarbon production.
Implementation Method 1
a distributed temperature sensor positioned on a fiber along an interval within the wellbore
Implementation Method 2
The injected fluid is typically colder than the formation temperature and a formation layer that receives a greater fluid flow rate during the injection has a longer 'warm back' time
Data Source
AI summary
A method for determining flow distribution in a formation having a wellbore formed therein includes the steps of positioning a sensor within the wellbore, wherein the sensor generates a feedback signal representing at least one of a temperature and a pressure measured by the sensor, injecting a fluid into the wellbore and into at least a portion of the formation adjacent the sensor, shutting-in the wellbore for a pre-determined shut-in period, generating a simulated model representing at least one of simulated temperature characteristics and simulated pressure characteristics of the formation during the shut-in period, generating a data model representing at least one of actual temperature characteristics and actual pressure characteristics of the formation during the shut-in period, wherein the data model is derived from the feedback signal, comparing the data model to the simulated model, and adjusting parameters of the simulated model to substantially match the data model.