Hydrocarbon Processing - February 2022 - 25

Special Focus Digital Technologies
R. KUMAR, P. K. RAKSHIT, M. JOHN and R. K. VOOLAPALLI,
Bharat Petroleum Corp. Ltd., Corporate R&D Center,
Greater Noida, Uttar Pradesh, India
Web-based software for predicting crude compatibility
and optimization for increasing heavy oil processing
Refineries in oil-importing nations
The objective of this article is to protypically
process a blend of crude oils,
rather than a single crude oil, to ensure
that an optimum product mix can be obtained
at the minimum costs. To increase
margins, refineries are looking for ways
to co-process heavy crude oils with light
crude oils.1-4
Heavy crude oils contain
high amounts of paraffins or asphaltenes.
High paraffin content results in high
viscosity and high pour point, making
transportation difficult. Conversely, high
asphaltene content causes precipitation,
flocculation, instability and incompatibility
challenges during processing. This
severely affects process equipment like
heat exchangers, pumps and tanks.5-8
The current benchmark process
to
determine compatibility of blending two
crude oils consists of 9-10 standard laboratory-based
test methods, out of which
3-4 are required to be done as per their
applicability range. These tests can take
weeks to complete. At present, there is no
standard practice to check the compatibility
parameter in advance; rather, chemical
dosing is done to prevent incompatibilityrelated
problems in refineries. Therefore,
increasing co-processing of heavy oil
components is a real challenge.
To increase the heavy oil content in the
mix of crude oils, and for suitable oil selection
for co-processing, refiners encounter
several common problems on day-to-day
operations. These include:
* Incompatibility/stability issues
when the crude oils are blended
* High viscosity of the blend
* High pour point of the blend
* High sulfur content in the blend
* High acidity and nitrogen content
* Low distillate yields and availability
for feedstock choices.
vide a quick and effective method for predicting
crude oil blend compatibility, as
well as for optimizing heavy oil processing,
using a prediction model softwarea
and blend optimization becomes even
more complicated.2
Therefore, another objective of this
.
The prediction model is based on the
measurement of a few bulk physical parameters,
which are conventionally and
regularly analyzed in a refinery's qualitycontrol
laboratory. This analysis typically
takes less than 1 hr, with no additional
tests required, which enables refiners to
quickly make blending decisions.
In contrast to conventional methods,
the present subject matter does not require
comprehensive laboratory testing
for compatibility and blending, which
otherwise normally takes several weeks.
Using the prediction model softwarea
, operators
can increase heavy oil processing
and substantially eliminate operational
problems related to asphaltene precipitation
caused by crude blend incompatibility.
Furthermore, conventional laboratory
test methods can optimize the blending of
only two crude oils at a time. To optimize
a blend of three crude oils, a compatible
blend test of two crude oils must be obtained,
followed by a compatibility test of
the first two blended crude oils with the
third. If additional crude oils need to be
blended, then the compatibility checking
article is to devise a methodology for
compatibility prediction and for the optimization
of blends having any number of
crude oils. The focus of this work can be
used for increasing heavy oil processing
and can help eliminate problems caused
by crude oil incompatibility.
Methodology. Asphaltene precipitation
has been a common problem in refineries.
It occurs due to incompatibility of the
crude mix, especially when the heavy oil
fraction increases in the blend. The quick
and reliable prediction of crude oil blending
compatibility is critical for the best
selection of crude oil blends.
The compatibility of crude oil blends
can be estimated using the following
tests: the colloidal instability index (CII),
the colloidal stability index (CSI), the
Stankiewicz plot (SP), qualitative-quantitative
analysis (QQA), the stability cross
plot (SCP), the Heithaus parameter (or
parameter P), heptane dilution (HD)/
toluene equivalence (TE), the spot test
and the oil compatibility model (OCM),
among others.9-13
All these experimental
methods are based on the physical model
of asphaltenes and their solubility with
FIG. 1. Physical model of asphaltene precipitation.
Hydrocarbon Processing | FEBRUARY 2022 25
Hydrocarbon Processing - February 2022

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