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Shale oil content forecasting method for Log-delta T logging evaluation

A prediction method, mud shale technology, applied in the field of well logging exploration, can solve the problems of low neutron and relatively low, achieve the effect of rapid calibration, cancel the tedious and difficult process

Inactive Publication Date: 2015-07-22
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

However, there is no suitable logging method to predict the key parameter of shale oil, that is, the residual oil content of shale, and the hydrocarbons (residual oil) in mud shale will cause abnormal responses of logging data, such as formation High resistance, high gamma, low neutron and relatively low density, etc., so how to extract the signal of residual hydrocarbon from these logging information and their combination information, and realize the prediction of the residual hydrocarbon amount of mud shale in unknown wells , to realize the evaluation of key parameters (residual hydrocarbons) of shale oil and gas

Method used

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  • Shale oil content forecasting method for Log-delta T logging evaluation
  • Shale oil content forecasting method for Log-delta T logging evaluation
  • Shale oil content forecasting method for Log-delta T logging evaluation

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Effect test

Embodiment 1

[0038] Embodiment 1: as figure 1 , figure 2 , image 3 , Figure 4 As shown, a logR-ΔT logging evaluation method for shale oil content prediction,

[0039] Shale formation oil content S 1 The steps for evaluating predictions are:

[0040] Step 1. Logging parameter preprocessing:

[0041] ① Extract acoustic transit time logging data ΔT and resistivity logging data R. The unit of ΔT is milliseconds per foot (μs / ft), and the unit of R is ohm-meter (Ω·m).

[0042]② Take the logarithm of the resistivity R to obtain logR;

[0043] Step 2. Node identification:

[0044] Identify the local minimum value from the resistivity R log curve and the acoustic time difference ΔT log curve, and remove the influence of non-residual hydrocarbon-containing intervals; mathematically, the method of derivation is usually used to find the minimum value, so It is necessary to derive the log curve;

[0045] The formula for calculating the first derivative of logR at the i-th depth point is:

...

Embodiment 2

[0079] Embodiment 2: as figure 1 , figure 2 , image 3 , Figure 4 As shown, a LogR-ΔT logging evaluation method for shale oil content prediction is illustrated by taking Well Luo 69 in the Bonan subsag as an example, and the following steps are adopted:

[0080] 1. Logging parameter preprocessing

[0081] ① Extract acoustic transit time logging data ΔT and resistivity logging data R. The unit of ΔT is milliseconds per foot (μs / ft), and the unit of R is ohm-meter (Ω·m).

[0082] ② Take the logarithm of the resistivity R to obtain logR;

[0083] 2. Node identification

[0084] From the resistivity R logging curve and the acoustic time difference ΔT logging curve, the local minimum value is identified, and the influence of the non-residual hydrocarbon layer is removed. The method of derivation is usually used to find the minimum value in mathematics, so the derivation of the logging curve is required;

[0085] The calculation formula of the first derivative of logR at th...

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Abstract

The invention discloses a shale oil content forecasting method for LogR-delta T logging evaluation and belongs to the technical field of logging exploration. The shale oil content forecasting method comprises the following steps: (1) preprocessing logging data; (2) performing minimum value joint identification; (3) performing logging curve leveling processing; (4) calibrating forecasted shale stratum oil content S1 and chloroform bitumen 'A' formula parameters; and (5) evaluating non-measured data shale stratum shale oil S1 and chloroform bitumen 'A' content in a quantitative mode, and achieving continuous forecasting and evaluation on the shale stratum shale oil content S1 and the chloroform bitumen 'A' without sampling. By means of the shale oil content forecasting method, fast calibration on a content model of the shale oil content S1 (or chloroform bitumen 'A') can be achieved by performing calibrating fitting on measured data directly through processed interval transit time and resistance data and forecasting on S1 (or chloroform bitumen 'A') of the non-measured oil content S1 (or chloroform bitumen 'A') can be achieved through logging data.

Description

technical field [0001] The invention relates to a mud shale oil content prediction method for LogR-ΔT logging evaluation. It belongs to the technical field of well logging exploration. Background technique [0002] In practical application, the shale oil content in mud shale mainly refers to chloroform bitumen "A" and S 1 relative content. It is one of the key indicators for the evaluation of unconventional oil and gas resources, and is directly related to the evaluation of the exploration potential of oil and gas resources. The current shale oil and gas is becoming a new bright spot in the exploration and development of global oil and gas resources. Shale oil and gas is a kind of self-generation and self-storage oil and gas resources. The conventional interpretation principle of evaluating the oiliness of sandstone by conventional logging cannot meet the requirements of residual oil and gas in shale. predict. However, conventional logging responses have different sensit...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): E21B49/00
Inventor 王民黄文彪薛海涛王伟明王文广刘敏陈国辉刘超
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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