IP Library › Granted Patent US 12692788

Granted Patent B2

US 12692788 · App. 18/725,452 · Granted Jul 28, 2026

Determination of asphaltene onset condition of reservoir fluids during downhole fluid analysis

Inventors: Shahnawaz Hossain Molla (Cambridge, MA); Elham Mahmoodaghdam (Houston, TX)

Assignee: Schlumberger Technology Corporation

E21B49/10 E21B47/06 E21B49/0875 E21B2200/22

View Patent ↗

Loading inventors, assignments & file history…

Monitor This Case

Get email alerts when status or documents change.

Order Certified Copies

Most orders are placed with the USPTO same day — all within 24 business hours.

Order via The Patent Place →

Pre-filled with this patent's details

Quick Facts

Patent No.: US 12692788
App. No.: 18/725,452
Granted: Jul 28, 2026
Kind: B2

External Links

USPTO Patent Center↗ Full Patent PDF↗

Abstract

Systems and methods for identifying a likelihood of problematic reservoir fluid containing asphaltene and/or an asphaltene onset pressure (AOP) using downhole fluid analysis data are provided. A method may include retrieving downhole fluid analysis data corresponding to a reservoir fluid that was obtained by a downhole acquisition tool positioned in a wellbore. The method may also include using a statistical model trained using historical downhole fluid analysis data and laboratory measurements to identify, based on the downhole fluid analysis data corresponding to the reservoir fluid, a likelihood of whether the reservoir fluid contains asphaltenes or an asphaltene onset pressure (AOP) of the reservoir fluid.

Claims (42)

1 . A method comprising:

receiving historical downhole fluid analysis data and historical laboratory measurements, wherein the historical downhole fluid analysis data comprises a pressure, a reservoir temperature, a carbon content, a fluid density, a fluid viscosity, or any combination thereof;

identifying a portion of the historical downhole fluid analysis data by removing one or more first datasets outside a range of values and removing one or more second datasets that are not part of the historical laboratory measurements;

identifying downhole fluid analysis data from the testing data, wherein the downhole fluid analysis data corresponds to a reservoir fluid that was obtained by a downhole acquisition tool positioned in a wellbore;

using a statistical model trained using the training data to identify, based on the downhole fluid analysis data corresponding to the reservoir fluid, a likelihood of whether the reservoir fluid contains problematic asphaltenes or an asphaltene onset pressure (AOP) of the reservoir fluid; and

verifying the statistical model is accurate based on the testing data.

2 . The method of claim 1 , wherein the method is performed before a sample of the reservoir fluid is analyzed in a laboratory.

3 . The method of claim 1 , wherein the method is performed while the downhole acquisition tool is positioned in the wellbore.

4 . The method of claim 1 , wherein the statistical model comprises a classification model, and the historical laboratory measurements comprise a determination of whether historical reservoir fluid samples contained the problematic asphaltenes.

5 . The method of claim 1 , wherein the statistical model comprises a regression model, and the historical laboratory measurements comprise measurements of a plurality of asphaltene onset pressures associated with a plurality of historical reservoir fluid samples.

6 . The method of claim 1 , comprising adjusting the downhole fluid analysis data to match a format of the historical downhole fluid analysis data used to train the statistical model.

7 . The method of claim 1 , comprising adjusting production of hydrocarbons from the wellbore based on whether the reservoir fluid is identified by the statistical model as being likely to contain the problematic asphaltenes.

8 . A system comprising:

a downhole acquisition tool comprising a downhole fluid analysis module configured to obtain downhole fluid analysis data corresponding to a reservoir fluid; and

processing circuitry configured to:

receive first historical downhole fluid analysis data and first historical laboratory measurements, wherein the first historical downhole fluid analysis data comprises a pressure, a reservoir temperature, a carbon content, a fluid density, a fluid viscosity, or any combination thereof;

identify a portion of the first historical downhole fluid analysis data by removing one or more first datasets outside a range of values and removing one or more second datasets that are not part of the first historical laboratory measurements;

partition the portion of the first historical downhole fluid analysis data into training data and testing data, wherein the testing data comprises at least one dataset corresponding to a first historical laboratory measurement of the first historical laboratory measurements classified as having asphaltene;

identify the downhole fluid analysis data from the testing data;

implement a first statistical model trained using the training data to identify, based on the downhole fluid analysis data corresponding to the reservoir fluid, a likelihood of whether the reservoir fluid contains problematic asphaltenes or an asphaltene onset pressure (AOP) of the reservoir fluid; and

verify the first statistical model is accurate based on the testing data.

9 . The system of claim 8 , wherein:

the first statistical model is configured to identify the likelihood of whether the reservoir fluid contains the problematic asphaltenes; and

the processing circuitry is configured to implement a second statistical model trained using second historical downhole fluid analysis data and second historical laboratory measurements to estimate the AOP.

10 . The system of claim 8 , wherein the first statistical model is trained using the first historical downhole fluid analysis data and the first historical laboratory measurements to provide a binary answer of whether the reservoir fluid contains the problematic asphaltenes.

11 . The system of claim 8 , wherein the first statistical model is trained using the first historical downhole fluid analysis data and the first historical laboratory measurements to provide a plurality of possible levels of confidence that the reservoir fluid contains the problematic asphaltenes.

12 . The system of claim 8 , wherein the first statistical model is trained using the first historical downhole fluid analysis data and the first historical laboratory measurements to provide a percentage level of confidence that the reservoir fluid contains the problematic asphaltenes.

13 . The system of claim 8 , wherein the first statistical model comprises a classification model configured to identify the likelihood of whether the reservoir fluid contains the problematic asphaltenes.

14 . The system of claim 8 , wherein the first statistical model comprises a regression model configured to identify the AOP of the reservoir fluid.

15 . A method comprising:

collecting, for respective samples of a plurality of samples of reservoir fluids, historical downhole fluid analysis data and historical laboratory measurements, wherein the historical downhole fluid analysis data comprises a pressure, a reservoir temperature, a carbon content, a fluid density, a fluid viscosity, or any combination thereof;

partitioning the portion of the historical downhole fluid analysis data into training data and testing data, wherein the testing data comprises at least one dataset corresponding to a first historical laboratory measurement of the historical laboratory measurements classified as having asphaltene and at least one dataset corresponding to a second historical laboratory measurement of the historical laboratory measurements classified as not having asphaltene;

training a model using the training data to identify a likelihood of whether a new reservoir fluid contains problematic asphaltenes or an asphaltene onset pressure (AOP) of the new reservoir fluid; and

verifying the model is accurate based on the testing data by comparing a result of the model to the at least one dataset corresponding to the first historical laboratory measurement of the historical laboratory measurements classified as having asphaltene and to the at least one dataset corresponding to the second historical laboratory measurement of the historical laboratory measurements classified as not having asphaltene.

16 . The method of claim 15 , wherein the portion of the historical downhole fluid analysis data is adjusted to exclude historical data corresponding to outlier samples of reservoir fluids having features that are not measurable by a downhole fluid analysis module but which can affect a presence of the problematic asphaltenes.

17 . The method of claim 15 , wherein the portion of the historical downhole fluid analysis data is adjusted to exclude historical data corresponding to outlier samples of reservoir fluids having hydrogen sulfide (H 2 S).

18 . The method of claim 16 , wherein the portion of the historical downhole fluid analysis data is adjusted to exclude components of the historical data that substantially do not impact the presence of the problematic asphaltenes.

19 . The method of claim 1 , wherein the testing data comprises at least one dataset corresponding to a second historical laboratory measurement of the historical laboratory measurements classified as not having asphaltene.

20 . The method of claim 19 , wherein verifying the statistical model is accurate based on the testing data comprises comparing a result of the statistical model to the at least one dataset corresponding to the first historical laboratory measurement of the historical laboratory measurements classified as having asphaltene and to the at least one dataset corresponding to the second historical laboratory measurement of the historical laboratory measurements classified as not having asphaltene.