JP4009534B2 - Multivariate analysis by mass spectrometry - Google Patents

Description

【００２１】
式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１２０種の分子グループを用いて、性能を未知の原油スレートから得られる減圧残渣のＨＲ／ＭＳフィンガープリントを生成させる。
【００２２】
式Ｃ_ｎＨ_{（２ｎ±ｚ）}で示される２４種の炭化水素分子グループを評価する。分子グループのうち１７種（全体の７１％）は、アスファルトレオロジーランクの関数として強度差を呈する。グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトは、低芳香族性炭化水素分子グループ（ｚ≦８）に関し強度差を示さない。グループＩＶのアスファルトは一般に、グループＩ、ＩＩまたはＩＩＩのアスファルトよりも、芳香族性が中程度の炭化水素分子グループ（１０≦ｚ≦２６）に関しより小さい強度を呈する。グループＩＶアスファルトは一般に、グループＩ、ＩＩまたはＩＩＩのアスファルトよりも、高芳香族性炭化水素分子グループ（２８≦ｚ≦４４）に関しより大きい強度を呈する。
【００２３】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒが単一硫黄置換である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１９種の分子グループを評価する。分子グループのうち１０種（全体の５３％）は、４つのアスファルトグループ間で強度差を呈する。グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトは、低芳香族性硫黄分子グループ（ｚ≦１０）に関し強度差を呈しない。グループＩＩＩおよびグループＩＶのアスファルトは一般に、グループＩおよびグループＩＩのアスファルトよりも、芳香族性が中程度の硫黄分子グループ（１２≦ｚ≦２２）に関しより小さい強度を呈する。グループＩＶのアスファルトは一般に、グループＩ、ＩＩまたはＩＩＩのアスファルトよりも、高芳香族性硫黄分子グループ（２４≦ｚ≦３４）に関しより大きい強度を呈する。
【００２４】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルト、Ｒ＝Ｓ_２である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１０種の分子グループを評価する。１０種の分子グループのうち３種（全体の３０％）は、４つのアスファルトグループ間で強度差を呈する。データが大きな変動を呈することに注意しなければならない。一般に、グループＩＶのアスファルトは、グループＩ、ＩＩまたはＩＩＩのアスファルトよりも、高芳香族性Ｓ_２分子グループ（１４≦ｘ≦２０）に関しより大きい強度を呈する。
【００２５】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒが単原子酸素置換である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される２０種の分子グループを評価する。２０種の分子グループのうち１２種（全体の６０％）は、４つのアスファルトグループ間で強度差を呈する。ジスルフィド分子グループのときと同じように、酸素分子グループは、各アスファルトグループ内で強度に大きな変動を呈する。グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトは、低芳香族性酸素分子グループ（ｚ≦１０）に関し強度差を示さない。グループＩＶのアスファルトは、グループＩ、ＩＩおよびＩＩＩのアスファルトよりも、芳香族性が中程度の酸素分子グループ（１２≦ｚ≦２０）に関しより小さい強度を呈する。グループＩＩＩおよびＩＶのアスファルトは、グループＩまたはＩＩのアスファルトよりも、高芳香族性酸素分子グループ（２２≦ｚ≦３２）に関しより低い強度を呈する。ｚ＞３２である分子グループの場合、４つのアスファルトグループ間で強度差はない。
【００２６】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒ＝Ｏ_２である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１４種の分子グループを評価する。２０種の分子グループのうち１２種（８５．７％）は、４つのアスファルトグループ間で強度差を呈する。Ｓ_２および単原子酸素分子グループのときと同じように、Ｏ_２分子グループは、各アスファルトグループ内で強度に大きな変動を呈する。Ｏ_２分子グループ（４≦ｚ≦２２）の場合、グループＩ、ＩＩおよびＩＩＩのアスファルトは、グループＩＶのアスファルトよりも大きい強度を呈する。
【００２７】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒが単原子窒素置換である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１７種の分子グループを評価する。窒素分子グループの強度と４つのアスファルトグループのレオロジー性能との間には、なんら傾向はみられない。
【００２８】
Ｒ＝ＳＯである式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される５種の高芳香族性分子グループを評価する。５つのグループは全て（１００％）、レオロジー性能ランクの関数として強度を呈する。グループＩ、ＩＩおよびＩＩＩのアスファルトは、Ｒ＝ＳＯかつ（１６≦ｚ≦２０）であるＣ_ｎＨ_{（２ｎ±ｚ）}−Ｒに関しより大きい強度を呈する。グループＩＩＩおよびＩＶのアスファルトは、グループＩおよびＩＩのアスファルトよりも、（２２≦ｚ≦２６）に関しより小さい強度を呈する。
【００２９】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒ＝ＮＯである式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される５種の分子グループを評価する。５種の分子グループは全て（１００％）、４つのアスファルトグループ間で強度差を呈する。グループＩ、ＩＩおよびＩＩＩのアスファルトは、グループＩＶのアスファルトよりも、ＮＯ分子グループ（９≦ｚ≦２１）に関しより大きい強度を呈する。
【００３０】
グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトについて、Ｒ＝Ｏ_３、ＳＯ_２、またはＮＯ_２である式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される種々の分子グループを評価する。グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトは、Ｏ_３分子グループでもＮＯ_２分子グループでも強度差を示さない。グループＩおよびＩＩのアスファルトは、第グループＩＩＩおよびＩＶのアスファルトよりも、ＳＯ_２分子グループに関しわずかに大きい強度を呈する。
【００３１】
１１種の異なる原油スレートから得られた３１種の減圧残渣に関しＨＲ／ＭＳフィンガープリントを作成した。レオロジー指数およびレオロジーパラメーターは、図４に示される１０種の原油スレートから得られた２７種の残渣のサブセットで利用可能であった。（ＭＥＮ＝Ｍｅｎｅｍｏｔｏ；ＢＣＦ−２２＝Ｂａｃｈｅｑｕｅｒｏ−２２；ＣＬ＝Ｃｏｌｄ ｌａｋｅ；ＢＲ＝Ｂｏｗ Ｒｉｖｅｒ；ＡＨＦ＝Ａｒａｂｉａｎ Ｈｅａｖｙ／Ｆｏｒｔｉｅｓブレンド）
【００３２】
それぞれの原油スレートの全体的序数型ランクは、その原油スレートから得られた減圧残渣の平均序数型ランクを求めて、その平均の平均値を計算することにより決定した。
【００３３】
それぞれのグループに属するアスファルトの分子組成を調べて４つのグループ間に差異があるかを決定した。この差異は、式Ｃ_ｎＨ_{（２ｎ±ｚ）}−Ｒで示される１２０種の分子グループのＨＲ／ＭＳフィンガープリントを用いるレオロジー性能の差異と一致した。グループＩ、ＩＩ、ＩＩＩおよびＩＶアスファルトについて、平均強度および標準偏差を計算した。９５％信頼区間を用いて、グループＩ、ＩＩ、ＩＩＩおよびＩＶのアスファルトで、それぞれの分子グループの強度の範囲を予測した。
【００３４】
それぞれのレオロジーグループの強度、芳香族性、炭素数および分子量の平均値に基づいて、少なくとも１２０種の分子グループのライブラリーを用いて次の関数関係について分子プロフィールをプロットした。
（ａ）強度＝ｆ（分子グループ、芳香族性）
（ｂ）芳香族性＝ｆ（分子グループ、強度）
（ｃ）平均アルキル側鎖長＝ｆ（分子グループ、芳香族性）
（ｄ）平均分子量＝ｆ（分子グループ、芳香族性）
【００３５】
分子プロフィールを比較することにより、良好なアスファルト（グループＩ）と不十分なアスファルト（グループＩＶおよびＶ）と間の分子組成の統計的有意差を明確化した。これに基づいて最適アスファルト組成を規定した。上記の関数関係のそれぞれについて、以下の分子モーメント（曲線下側の一次面積モーメント）を計算する。
（ａ）Ｒｉ＝分子グループＲの強度モーメント
（ｂ）Ｒｚ＝分子グループＲの芳香族性モーメント
（ｃ）Ｒｃ＝分子グループＲの平均アルキル側鎖長モーメント
（ｄ）Ｒｍ＝分子グループＲの平均分子量
【００３６】
グループＩおよびグループＩＶのアスファルトのＨＲ／ＭＳフィンガープリントの差異を図１に例示する。アスファルトは、それらの原料の原油または原油ブレンドに基づき、相対的フィールド性能に関してランクづけすることができる。レオロジーランクづけシステムは、アスファルトが組み込まれた舗道の性能を正確に反映および予測する経験的および機械的アスファルトバインダー試験から得られる性能パラメーターの組み合わせに基づく。レオロジーランクづけシステムにより同定される異なるアスファルトグループ（即ち、グループＩ、ＩＩ、ＩＩＩおよびＩＶ）は、異なる分子組成を呈する。１つのレオロジーグループに属するアスファルトの分子組成は類似している。アスファルトグループ間の分子組成の差異には一貫性がある。アスファルトのレオロジー性能およびフィールド性能は、その分子組成により予測することができる。
【００３７】
アスファルトのレオロジー性能および舗装性能は、有益な性質を有する成分の濃度を最大化し、有害なまたは他の非有益な性質を有する成分の濃度を最小化するアスファルトおよび原料の原油または原油ブレンドを選択することにより最適化することができる。
【００３８】
予備的フィンガープリント測定を行うために、８５／１００領域に針入度を有するＭｅｎｅｍｏｔｏ（ＭＥＮ）、Ｂｏｕｎｄａｒｙ Ｌａｋｅ（ＢＬ）およびＣｏｌｄ Ｌａｋｅ（ＣＬ）アスファルト／減圧残渣のようにアスファルトの製造に利用される典型的な重質原油を選択した。３種のアスファルトは、明確に異なる舗装性能を呈する。最初のＨＲ／ＭＳフィンガープリントは、極性−１留分で作成した。スルホキシド、カルボン酸、フェノールおよびピリジンを、骨材への接着の主要因となる極性官能基として、ＳＨＲＰ Ａ３４１文書に基づいて同定した。
【００３９】
３種の代表的な原油に由来する留分のＨＲ／ＭＳフィンガープリントを図２に示す。反復なし、有意水準データ０．０５で、Ｅｘｃｅｌ ５．０ Ｔｗｏ Ｆａｃｔｏｒ Ａｎａｌｙｓｉｓ ｏｆ Ｖａｒｉａｎｃｅ（ＡＮＯＶＡ）を用いて、データの統計的有意性を分析した。分析の結果、ＨＲ／ＭＳフィンガープリント法により、組み合わせヘテロ原子フラグメントに基づいて０．０５の有意水準で３種のアスファルトを区別しうることが示唆された。ＭＥＮ残渣は、他の２種のアスファルトよりも、評価対象の分子種に関しより大きい強度を呈したことから、より極性の大きい材料であることが示唆された。ＣＬおよびＢＬアスファルトは、硫化物強度の差により区別された。
【００４０】
予備実験の結果から、アスファルトのフィンガープリントが取得可能であることおよび異なる品質のアスファルトが異なる濃度の分子フラグメントを呈することが実証された。特定のフラグメントの有意性またはアスファルト性能へのその寄与率は決定されなかった。
【００４１】
第二世代ＨＲ／ＭＳフィンガープリントは、組み合わせヘテロ原子の拡張物質ライブラリーに基づくものであり、芳香族留分および極性−１留分の両方を含み、評価対象のアスファルトの割合を効果的に５０重量パーセントよりも大きくした。正規型分子フラグメント分布を用いて第二世代ＨＲ／ＭＳフィンガープリントを構築した。単一の針入度グレードまたはＳＵＰＥＲＰＡＶＥ（登録商標） ＰＧグレードに属する全てのアスファルト／残渣のフィンガープリントを評価し、どの官能基が統計的に特有のフィンガープリントを生成するかを決定した。
【００４２】
Ｍｅｎｅｍｏｔａ（ＭＥＮ）、Ｂａｃｈｅｑｕｅｒｏ−２２（ＢＣＦ−２２）およびＣｏｌｄ Ｌａｋｅ（ＣＬ）のように３種の異なる原油から得られた典型的な８５／１００針入度アスファルトのＨＲ／ＭＳフィンガープリントを図３に示す。Ｅｘｃｅｌ ５．０を用いてデータを検査し、異なる原料原油から得られたアスファルト間の統計的有意差が存在するかを確認した。分子種の全ライブラリーを用いたが、原料の異なるアスファルト間の統計的有意差は存在しなかった。第一世代フィンガープリントでうまく行くことが実証された組み合わせヘテロ原子サブセットを用いたが、統計的有意差は存在しなかった。酸素、窒素および組み合わせヘテロ原子基のサブセットを使用したとき、より軟質のアスファルトは統計的有意差を呈し、８５／１００針入度（ＳＵＰＥＲＰＡＶＥ ＰＧ ５８〜２２）アスファルトは、境界線上の差異を呈した。酸素、窒素および組み合わせヘテロ原子官能基が組み込まれたＨＲ／ＭＳフィンガープリントを用いると、改良された組成指数を開発することができる。図４は、質量スペクトルに及ぼす原油の組成変化の影響を示している。
【００４３】
ＨＲ／ＭＳに付す残渣試料は、好ましくは、所定の温度、所与の時間、一定の低圧で、正確に全原油を加熱することのできる装置を用いて調製される。装置は温度条件および減圧条件のいずれに対しても優れた長期間安定性を示すことが重要である。装置の温度および減圧度は変化させうるが、所定の圧力で目標大気圧換算温度（ＡＥＴ）に対応する温度が得られた後は、温度および圧力はいずれも、実験全体にわたって一定に保持される。実験時、周囲圧以下の圧力（減圧）にすると、アスファルト／残渣の熱分解が防止される。アスファルト／残渣を得るために、目標ＡＥＴに対応する正確な温度−圧力の組み合わせを決定することが必要である。ＡＳＴＭ Ｄ５２３６に概要されているようにこれを行うことができるが、その手順では、温度および圧力の両方を正確に測定することが必要である。この手順の実施中に装置の温度を測定することは簡単であるが、作動圧力を測定することは一般に難しい。圧力の直接測定を回避すべく、この方法では、１組の公知の原油の蒸留プロフィールを用いて温度−圧力条件に対して装置を校正する。プロセス温度の読取り値とＡＥＴとの相関は、校正物質原油の蒸留プロフィールを用いて決定される。
【００４４】
好ましい方法では、小型密閉チャンバーに秤量済み凍結原油試料を配置し、メカニカルポンプにより一次的にポンプダウンし、次いで小型密閉チャンバーから少なくとも１Ｌの容積を有する減圧レベル既知（例えば、１ｍＴｏｒｒ）のチャンバーへの通路（即ち、加熱マニホールド）を開放する。中間生成物、残油および経時アスファルトを、原油の代わりに使用するかまたは原油と混合することができる。好ましい試料サイズは１０〜４０ｍｇであるが、２〜２００ｍｇも本発明の一部をなすと見なされる。次に、平衡後に残存する残渣を取り出して再び秤量する。１回目の測定重量と２回目の測定重量の比がＡＥＴ収率となる。減圧チャンバーを連続的にポンプダウンするか、減圧チャンバーを所望の圧力に達した後に閉鎖した後試料に暴露するかに応じて減圧ポンプラインまたは減圧チャンバーから採取したガスを分析することにより、他の情報を決定することができる。
【００４５】
好ましい装置は、試料オーブン、試料ホルダーおよび全ガラス製加熱マニホールドを有する。装置は、１ｍＴｏｒｒ（１０^−３Ｔｏｒｒ）の絶対圧力を達成することができる。試料を石英管ボート中に秤量し、液体窒素浴中で冷却する。次に、それを試料ホルダー中に入れてマニホールドに取り付ける。マニホールド中の高温ガラスバルブを用いて試料を周囲圧以下の圧力に暴露する。他のボートを使用してもよいが、石英が好ましい。試料を減圧に暴露する際、試料オーブンを周囲温度から目標温度まで加熱し、その温度に所定の時間保持する。試料調製時間全体にわたり一定の高温（３００〜３５０℃）に保持されるマニホールドは、試料ホルダーと、装置により生成される減圧との間の物理的インターフェースを可能にする。この方法では、抜頭処理される各原油に対して減圧を発生させたり分配したりする必要はない。これにより、全原油からのアスファルト／残渣の試料調製時間が大幅に削減される。
【００４６】
ＡＥＢＰおよび原油の性質にもよるが、この方法により、５ｍｌの全原油から約２０ｇのアスファルトまたは残渣が生成される。好ましい試料形態は、シート、薄膜および液滴である。これらの試料形態をとれば、試料を急速に冷却または加熱するための十分に大きな表面積が得られる。オーブンの減圧度が高くなるほど（圧力が低くなるほど）、オーブン温度を低くすることができるので、試料の分解を低減させることができる。本発明の好ましい態様では、１５分以下の試料平衡時間、定減圧度緩衝器および０．２％の繰り返し精度を有する固定温度オーブンを使用する。「凍結」という用語は、試料の損傷を引き起こすほどの水の気化が少なくとも３０〜６０秒間起こらないように、十分に低い温度まで冷却することを意味する。
【図面の簡単な説明】
【図１】 グループＩ〜ＩＶのアスファルトのフィンガープリントスペクトル（強度ｖｓ質量）を示している。
【図２】 ３種の代表的な原油（ＭＥＮ、ＣＬおよびＢＬ）に由来する留分のフィンガープリントスペクトル（強度ｖｓ質量）を示している。
【図３】 ３種の代表的な原油（ＭＥＮ、ＢＣＦ−２２およびＣＬ）から得られたアスファルトのフィンガープリントスペクトル（強度ｖｓ質量）を示している。
【図４】 グループＩ〜Ｖのレオロジーグループ（ＲＧ）について、炭素数、分子量および強度ｖｓ質量を示している。[0001]
This application is a provisional patent application based on US application Nos. 60 / 258,900, 60 / 256,129 and 60 / 258,899 (filed on Dec. 15, 2000). Insist.
[0002]
Background of the Invention
Multivariate models include component concentrations such as benzene content, saturates content, aromatics content and olefin content in automotive gasoline, diesel fuel, jet fuel and process streams, gasoline research and motor octane numbers, and diesel fuel. This is a model that is fundamental in estimating properties such as cetane number from an infrared spectrum using an on-line infrared analyzer. For example, Maggard describes the use of a multivariate model to determine the content of paraffins, isoparaffins, aromatics, naphthenes and olefins in motor gasoline and gasoline components (US Pat. No. 5,349,189). . Maggard also describes the use of MLR to measure octane and cetane numbers (US Pat. No. 4,963,745 and US Pat. No. 5,349,188). Perry and Brown (US Pat. No. 5,817,517) describe the use of FT-IR to determine the composition of the feed sent to the hydrocarbon conversion, separation and blending processes.
[0003]
The use of multivariate models is not limited to infrared analyzers. Jeff describes the use of gas chromatography to estimate the octane number of gasoline (US Pat. No. 4,251,870). Ashe, Roussis, Fedora, Felsky and Fitzgerald describe the use of gas chromatography / mass spectrometry (GC / MS) and multivariate modeling to predict the chemical or physical properties of crude oil (US Pat. No. 5 , 699, 269). Cooper, Bledsoe, Wise, Sumner and Welch describe the use of Raman spectroscopy and multivariate modeling to estimate gasoline octane number and reed vapor pressure (US Pat. No. 5,892,228).
[0004]
Conventional asphalt binder standards deal with binder properties such as penetration, viscosity, ductility, softening point, etc. with a history of empirical correlation with asphalt pavement performance during use. Standards based on conventional properties have not been able to provide a stable and durable road surface, so based on rheological performance under limited frequency and temperature conditions, SUPERPAVE for rheologically simple asphalt binders ( (Registered Trademark) standards have been developed. The SUPERPAVE® standard currently does not deal with rheologically complex materials, and the performance of asphalt with the same performance grade (PG) is not currently distinguished.
[0005]
Attempts to rank molecular components based on conventional and SUPERPAVE® type performance parameters and identify “ideal” asphalt compositions have not been successful. Using a single performance parameter to rank the performance of each asphalt or vacuum residue hides the relationship between composition and performance. The assigned rank is which parameter to select (ie penetration at 25 ° C., SUPERPAVE width between PG temperatures (Tmax and Tmin), G at Tg) ^* Etc.) will vary greatly. The assigned rank has also been found to be too influenced by the distillation cut temperature of the residue.
[0006]
It would be beneficial to find a way to rank and accept an acceptable or ideal asphalt composition by testing the feedstock or blend under consideration prior to asphalt manufacture.
[0007]
Summary of the Invention
In accordance with the present invention, a combination of conventional and rheological parameters provides a composite rheological rank that accurately predicts the relative field performance of asphalt. With this rank, rheologically similar asphalts and vacuum residues share a common point with respect to the molecular composition, preferably measured by high resolution mass spectrometry. A high abundance of a particular molecular structure suggests excellent asphalt pavement performance.
[0008]
Detailed Description of the Invention
A method to quickly predict and improve the asphalt quality of unknown crude oil was developed. To achieve that goal, a clear relationship between molecular composition and asphalt pavement performance is required. High resolution mass spectrometry (HR / MS) was used to establish a relationship between crude oil slate and asphalt molecular composition independent of penetration and performance grade. Formula C _n H _{(2n ± z)} A molecular structure represented by -R, wherein n is generally greater than 10, z is from 0 to about 44, and R is a heteroatom or combination of heteroatoms containing sulfur, nitrogen or oxygen Approximately 120 molecular groups having a Molecular groups are used to distinguish asphalt from different crude oil slate and are less affected by the distillation cut temperature of residues from the same crude oil slate. The relationship between asphalt composition and pavement performance is established by empirical (by standards) and mechanical (rheological) measurements on asphalt binders in the laboratory.
[0009]
The present invention is a method for determining the suitability of crude oils, mixtures of different crude oils (crude oil slate) and crude oil fractions as raw materials for asphalt production based on the chemical concentrations of several HR / MS molecular fragments in the raw material sample. is there. Certain fingerprint regions contain individual molecular components that are expected to function properly in asphalt.
[0010]
The determination of the optimal asphalt composition from the molecular moment is preferably
a) selecting asphalt or residue;
b) performing a conventional test, a SUPERPAVE® test and / or a rheology test;
c) determining the rheological index of the sample;
d) determining an average rheological index (RI ′) of the crude oil slate;
e) assigning a rheology group (RG, eg, groups I-IV);
f) calculating the average intensity, aromaticity, carbon number and molecular weight for each RG;
g) For each molecular group (hydrocarbon, sulfur, oxygen, etc.), the average values of Z = f (I), I = f (Z), MW = f (Z), C # = f (Z) are plotted. The step of:
h) The molecular moment is expressed by the following formula:
Molecular moment = total of (strength x aromaticity) / total of (aromaticity)
Calculating by:
i) comparing the molecular profiles of good asphalt (Group I) and poor asphalt (Group IV); and
j) Confirming statistical significance of differences using molecular moments
Is achieved by a method comprising:
[0011]
The prediction of asphalt performance from the molecular composition is preferably
a) selecting asphalt or residue;
b) performing high resolution mass spectrometry;
c) calculating the average value of Z = f (I), I = f (Z), MW = f (Z), C # = f (Z) for each molecular group;
d) determining the predicted rheological index (RI) of the sample using the formula RI = f (moment);
e) comparing the predicted RI with that of good asphalt (Group I) and poor asphalt (Group IV);
f) determining the rheological group of the sample;
g) predicting the suitability of crude slate for asphalt production based on RG; and
h) Confirming the suitability of crude oil slate for asphalt production by comparing with Group I and Group IV asphalt.
Is achieved by a method comprising:
[0012]
A mathematical description of a preferred model for determining the rheological index (RI) in step (d) above is as follows.
RI = 13.8639-1.81864E-1 ^* Hc + 6.12843E-2Hi-4.153E-1Hz-4.68191E-3Ni + 6.6655E-3Oi + 5.88057E-3Sm-1.42995E-1Sz-3.14998E-3 [C5ARings-]-3.35754E-3 [C5ARings +] (Wherein R ² = 0.95).
[0013]
For asphalt production, the following molecular moment characteristics are preferred. Asphalt for pavement exhibiting good performance generally has a higher strength of hydrocarbon molecular groups with 10 ≦ z ≦ 26, and a lower strength with hydrocarbon molecular groups with 28 ≦ z ≦ 44, and 12 ≦ z. The strength of the sulfur molecular group of ≦ 22 is larger, the strength of the highly aromatic sulfur molecular group of 24 ≦ z ≦ 34 is smaller, and the formula C _n H _{(2n ± z)} -R at R = S ₂ Is highly aromatic S ₂ The intensity of the molecular group (14 ≦ x ≦ 20) is smaller and the formula C _n H _{(2n ± z)} Molecular group in which the intensity of oxygen molecular group (12 ≦ z ≦ 20) and highly aromatic oxygen molecular group (22 ≦ z ≦ 32) in which R is monoatomic oxygen substitution in -R is larger and z> 32 There is no difference in strength between asphalts. C where 4 ≦ z ≦ 22 _n H _{(2n ± z)} = O ₂ For molecular groups, good and medium asphalts exhibit greater strength than poor asphalts. C _n H _{(2n ± z)} For ═SO, good asphalt exhibits greater strength when 16 ≦ z ≦ 26. C _n H _{(2n ± z)} For ═NO, good asphalt exhibits greater strength than poor asphalt when 9 ≦ z ≦ 21. SO ₂ For molecular groups, good asphalt exhibits slightly greater strength than poor asphalt. FIG. 4 shows a comparison of these types.
[0014]
In the present invention, three classes of performance parameters are used to rank asphalt and vacuum residues and predict their pavement performance.
I. Conventional parameters can include properties and specifications such as penetration, viscosity, softening point, ductility, Canadian General Standards Board (CGSB) grade, Fraass point, n-heptane insolubles, elemental analysis, and the like.
II. SUPERPAVE (registered trademark) performance parameters: performance grade (PG XX-YY), SUPERPAVE (registered trademark) width (numerical difference between high temperature and low temperature standard temperature XX and YY), crossover temperature (Tmax, Tmin, and Tfat; standard) The temperature at which the rigidity limit is satisfied) and the crossover temperature width (Tmax-Tmin) can be included.
III. Rheological index obtained from complete rheological analysis within the linear viscoelastic region of the material: SHRP rheological model (master curve index Gg, η0, ωc and R at Tref = + 10 ° C.) and phase response index (Tf, Tb, T45 @ δ = 10 rad / s isochronous curve), black diagram characteristics and the like.
[0015]
Conventional asphalt properties, CGSB grade, SUPERPAVE® performance parameters and rheology index all describe the temperature sensitivity of asphalt by load bearing capacity, deformability, strain resistance and deformation recovery after load removal. Used as a purpose. Each parameter measures various aspects of the material response. In the present invention, a parameter combination method has been developed to fully describe the behavior of asphalt as a function of crude oil slate without depending on the distillation cut temperature.
[0016]
By an iterative process, parameters as shown in Table 1 were selected, and asphalt and vacuum distillation residues were ranked for pavement performance. Since the majority of these parameters are based on classical rheology, they are called rheological performance parameters.
[0017]
Based on values that optimize pavement performance in general applications, an ordinal or normal nominal ranking system is used for the parameters as shown in Table 1. A performance parameter is measured or calculated for each vacuum residue obtained from a given crude oil slate at a given cut temperature. Assign a rank for each parameter to the residue based on the parameter-by-parameter comparison. Allow duplicate ranks if the parameters are equivalent or identical. Based on the rank of that individual parameter, calculate the average rank of the residue. Determine the overall rank of each crude slate by calculating the average of the average ranks determined for all residues obtained from the crude slate in the previous step (FIG. 1). Based on the rheological rank, five pavement asphalt rheological “quality” groups are identified. Group I is a “good” asphalt, Group II is a “good” asphalt, Group III is a “satisfactory” asphalt, and Groups IV and V are “insufficient” and “very poor” It is asphalt.
[0018]
The molecular composition of asphalt belonging to each group has the formula C _n H _{(2n ± z)} Using HR / MS fingerprints of 120 molecular groups denoted -R is consistent with rheological performance. FIG. 3 shows an example of how different crudes produce asphalt with different compositions.
[0019]
Average intensity and standard deviation were calculated for Group I, II, III and IV asphalts.
[0020]
[Table 1]

[0021]
Formula C _n H _{(2n ± z)} 120 molecular groups denoted -R are used to generate a HR / MS fingerprint of vacuum residue obtained from crude slate with unknown performance.
[0022]
Formula C _n H _{(2n ± z)} 24 types of hydrocarbon molecular groups are evaluated. 17 of the molecular groups (71% of the total) exhibit intensity differences as a function of asphalt rheological rank. Group I, II, III and IV asphalts show no difference in strength with respect to the low aromatic hydrocarbon molecular group (z ≦ 8). Group IV asphalts generally exhibit less strength for moderately aromatic hydrocarbon molecular groups (10 ≦ z ≦ 26) than Group I, II or III asphalts. Group IV asphalts generally exhibit greater strength for high aromatic hydrocarbon molecular groups (28 ≦ z ≦ 44) than Group I, II or III asphalts.
[0023]
For groups I, II, III and IV asphalts, the formula C wherein R is a single sulfur substitution _n H _{(2n ± z)} The 19 molecular groups denoted by -R are evaluated. Ten of the molecular groups (53% of the total) exhibit strength differences between the four asphalt groups. Group I, II, III and IV asphalts do not exhibit a difference in strength with respect to the low aromatic sulfur molecular group (z ≦ 10). Group III and Group IV asphalts generally exhibit less strength with respect to moderately aromatic sulfur molecular groups (12 ≦ z ≦ 22) than Group I and Group II asphalts. Group IV asphalts generally exhibit greater strength for high aromatic sulfur molecular groups (24 ≦ z ≦ 34) than Group I, II or III asphalts.
[0024]
Group I, II, III and IV asphalts, R = S ₂ Is the formula C _n H _{(2n ± z)} The 10 molecular groups denoted by -R are evaluated. Of the ten molecular groups, three (30% of the total) exhibit strength differences between the four asphalt groups. It should be noted that the data exhibits large fluctuations. In general, Group IV asphalts are more highly aromatic than Group I, II or III asphalts. ₂ It exhibits greater strength with respect to molecular groups (14 ≦ x ≦ 20).
[0025]
For groups I, II, III and IV asphalts, the formula C wherein R is a monoatomic oxygen substitution _n H _{(2n ± z)} Twenty molecular groups represented by -R are evaluated. Twelve of the 20 molecular groups (60% of the total) exhibit strength differences between the four asphalt groups. As with the disulfide molecular group, the oxygen molecular group exhibits a large variation in strength within each asphalt group. Group I, II, III and IV asphalts show no difference in intensity with respect to the low aromatic oxygen molecular group (z ≦ 10). Group IV asphalts exhibit less strength with respect to moderately aromatic molecular oxygen groups (12 ≦ z ≦ 20) than Group I, II and III asphalts. Group III and IV asphalts exhibit lower intensity for highly aromatic molecular oxygen groups (22 ≦ z ≦ 32) than Group I or II asphalts. For molecular groups where z> 32, there is no intensity difference between the four asphalt groups.
[0026]
For group I, II, III and IV asphalts, R = O ₂ Is the formula C _n H _{(2n ± z)} The 14 molecular groups denoted by -R are evaluated. Of the 20 molecular groups, 12 (85.7%) exhibit strength differences between the four asphalt groups. S ₂ And as with the monoatomic oxygen molecule group, O ₂ Molecular groups exhibit large variations in strength within each asphalt group. O ₂ For molecular groups (4 ≦ z ≦ 22), Group I, II and III asphalts exhibit greater strength than Group IV asphalts.
[0027]
For groups I, II, III and IV asphalts, the formula C wherein R is a monoatomic nitrogen substitution _n H _{(2n ± z)} The 17 molecular groups denoted -R are evaluated. There is no trend between the strength of the nitrogen molecular group and the rheological performance of the four asphalt groups.
[0028]
Formula C where R = SO _n H _{(2n ± z)} Five types of highly aromatic molecule groups represented by -R are evaluated. All five groups (100%) exhibit strength as a function of rheological performance rank. Group I, II and III asphalts are C = R = SO and (16 ≦ z ≦ 20) _n H _{(2n ± z)} It exhibits greater strength with respect to -R. Group III and IV asphalts exhibit less strength with respect to (22 ≦ z ≦ 26) than Group I and II asphalts.
[0029]
For groups I, II, III and IV asphalts, the formula C where R = NO _n H _{(2n ± z)} The five molecular groups denoted by -R are evaluated. All five molecular groups (100%) exhibit strength differences between the four asphalt groups. Group I, II and III asphalts exhibit greater strength for the NO molecular group (9 ≦ z ≦ 21) than Group IV asphalts.
[0030]
For group I, II, III and IV asphalts, R = O ₃ , SO ₂ Or NO ₂ Is the formula C _n H _{(2n ± z)} The various molecular groups denoted -R are evaluated. Group I, II, III and IV asphalts are O ₃ NO even in the molecular group ₂ Even the molecular group shows no intensity difference. Group I and II asphalts are more SO 2 than Group III and IV asphalts. ₂ It exhibits a slightly greater intensity with respect to molecular groups.
[0031]
HR / MS fingerprints were generated for 31 vacuum residues obtained from 11 different crude oil slate. Rheology index and rheology parameters were available for a subset of 27 residues obtained from the 10 crude slate shown in FIG. (MEN = Menemoto; BCF-22 = Baquequero-22; CL = Cold lake; BR = Bow River; AHF = Arabian Heavy / Forties blend)
[0032]
The overall ordinal rank of each crude oil slate was determined by determining the average ordinal rank of the vacuum residue obtained from the crude oil slate and calculating the average of the averages.
[0033]
The molecular composition of asphalt belonging to each group was examined to determine if there was a difference between the four groups. This difference is expressed by the formula C _n H _{(2n ± z)} Consistent with the rheological performance differences using the HR / MS fingerprints of the 120 molecular groups denoted -R. Average intensity and standard deviation were calculated for Group I, II, III and IV asphalts. A 95% confidence interval was used to predict the intensity range of each molecular group on Group I, II, III and IV asphalts.
[0034]
Based on the average values of the strength, aromaticity, carbon number and molecular weight of each rheological group, molecular profiles were plotted for the following functional relationships using a library of at least 120 molecular groups.
(A) Strength = f (molecular group, aromaticity)
(B) Aromaticity = f (molecular group, strength)
(C) Average alkyl side chain length = f (molecular group, aromatic)
(D) Average molecular weight = f (molecular group, aromatic)
[0035]
Comparison of molecular profiles clarified the statistically significant difference in molecular composition between good asphalt (Group I) and poor asphalt (Groups IV and V). Based on this, the optimum asphalt composition was defined. For each of the above functional relationships, the following molecular moment (primary area moment below the curve) is calculated.
(A) Ri = Intensity moment of molecule group R
(B) Rz = aromatic moment of molecular group R
(C) Rc = Molecular group R average alkyl side chain length moment
(D) Rm = average molecular weight of molecular group R
[0036]
The differences in HR / MS fingerprints of Group I and Group IV asphalts are illustrated in FIG. Asphalts can be ranked in terms of relative field performance based on their raw crude oil or crude oil blend. The rheological ranking system is based on a combination of performance parameters derived from empirical and mechanical asphalt binder tests that accurately reflect and predict the performance of asphalt-incorporated pavements. Different asphalt groups identified by the rheological ranking system (ie, Groups I, II, III and IV) exhibit different molecular compositions. The molecular composition of asphalt belonging to one rheological group is similar. Differences in molecular composition between asphalt groups are consistent. The rheological and field performance of asphalt can be predicted by its molecular composition.
[0037]
Asphalt rheological and paving performance selects asphalt and raw crude or crude oil blends that maximize the concentration of components with beneficial properties and minimize the concentration of components with harmful or other non-beneficial properties Can be optimized.
[0038]
Used to make asphalt, such as Menemoto (MEN), Boundary Lake (BL) and Cold Lake (CL) asphalt / vacuum residue with penetration in 85/100 area to make preliminary fingerprint measurements A typical heavy crude was selected. The three types of asphalt exhibit distinctly different paving performance. The first HR / MS fingerprint was made with a polar-1 fraction. Sulfoxides, carboxylic acids, phenols and pyridines were identified based on the SHRP A341 document as polar functional groups responsible for adhesion to aggregates.
[0039]
The HR / MS fingerprints of the fractions derived from three representative crude oils are shown in FIG. The statistical significance of the data was analyzed using Excel 5.0 Two Factor Analysis of Variance (ANOVA) with no significance and 0.05 significance level data. Analysis suggested that the HR / MS fingerprinting method could distinguish the three asphalts at a significance level of 0.05 based on the combined heteroatom fragment. The MEN residue exhibited a higher strength with respect to the molecular species to be evaluated than the other two types of asphalt, suggesting that it is a more polar material. CL and BL asphalts were distinguished by differences in sulfide strength.
[0040]
Preliminary results have demonstrated that asphalt fingerprints can be obtained and that different quality asphalts exhibit different concentrations of molecular fragments. The significance of a particular fragment or its contribution to asphalt performance was not determined.
[0041]
The second generation HR / MS fingerprint is based on a combinatorial heteroatom extension material library, which includes both aromatic and polar-1 fractions, effectively reducing the percentage of asphalt to be evaluated. Greater than weight percent. A second generation HR / MS fingerprint was constructed using a normal molecular fragment distribution. All asphalt / residue fingerprints belonging to a single penetration grade or SUPERPAVE® PG grade were evaluated to determine which functional groups produced statistically unique fingerprints.
[0042]
The HR / MS fingerprint of a typical 85/100 penetration asphalt obtained from three different crude oils such as Menemota (MEN), Bachequero-22 (BCF-22) and Cold Lake (CL) is shown in FIG. Shown in The data was examined using Excel 5.0 to see if there was a statistically significant difference between asphalts obtained from different raw crude oils. Although a full library of molecular species was used, there was no statistically significant difference between asphalts of different raw materials. We used combinatorial heteroatom subsets that proved to work well with first generation fingerprints, but there was no statistically significant difference. When using a subset of oxygen, nitrogen and combined heteroatom groups, softer asphalts showed statistically significant differences and 85/100 penetration (SUPERPAVE PG 58-22) asphalts showed boundary differences . Improved compositional indices can be developed using HR / MS fingerprints incorporating oxygen, nitrogen and combined heteroatom functional groups. FIG. 4 shows the effect of changes in crude oil composition on the mass spectrum.
[0043]
Residue samples subjected to HR / MS are preferably prepared using equipment that can accurately heat the whole crude oil at a given temperature, a given time, and at a constant low pressure. It is important that the apparatus exhibits excellent long-term stability for both temperature and reduced pressure conditions. Although the temperature and degree of pressure reduction of the apparatus can be changed, after the temperature corresponding to the target atmospheric pressure conversion temperature (AET) is obtained at a predetermined pressure, both the temperature and the pressure are kept constant throughout the experiment. . During the experiment, if the pressure is lower than the ambient pressure (reduced pressure), thermal decomposition of asphalt / residue is prevented. In order to obtain asphalt / residue, it is necessary to determine the exact temperature-pressure combination corresponding to the target AET. While this can be done as outlined in ASTM D5236, the procedure requires that both temperature and pressure be accurately measured. Measuring the temperature of the device during this procedure is simple, but it is generally difficult to measure the operating pressure. In order to avoid direct pressure measurements, this method calibrates the device to temperature-pressure conditions using a set of known crude oil distillation profiles. The correlation between the process temperature reading and the AET is determined using the calibrator crude oil distillation profile.
[0044]
In a preferred method, a weighed frozen crude oil sample is placed in a small sealed chamber, pumped down primarily by a mechanical pump, and then from a small sealed chamber to a chamber of known pressure reduction level (eg, 1 mTorr) having a volume of at least 1 L. Open the passage (ie, the heating manifold). Intermediate products, residual oils and timed asphalt can be used instead of crude oil or mixed with crude oil. The preferred sample size is 10-40 mg, but 2-200 mg is considered part of the present invention. Next, the residue remaining after equilibration is taken out and weighed again. The ratio between the first measured weight and the second measured weight is the AET yield. Depending on whether the vacuum chamber is continuously pumped down or the vacuum chamber is closed after reaching the desired pressure and then exposed to the sample, other gases can be analyzed by analyzing the gas collected from the vacuum pump line or vacuum chamber. Information can be determined.
[0045]
A preferred apparatus has a sample oven, a sample holder and an all-glass heating manifold. The apparatus is 1 mTorr (10 ^-3 An absolute pressure of Torr) can be achieved. The sample is weighed into a quartz tube boat and cooled in a liquid nitrogen bath. It is then placed in the sample holder and attached to the manifold. Expose the sample to sub-ambient pressure using a hot glass bulb in the manifold. Quartz is preferred, although other boats may be used. When exposing the sample to reduced pressure, the sample oven is heated from ambient temperature to the target temperature and held at that temperature for a predetermined time. A manifold maintained at a constant high temperature (300-350 ° C.) throughout the sample preparation time allows a physical interface between the sample holder and the vacuum generated by the device. In this method, it is not necessary to generate or distribute a reduced pressure for each crude oil to be decapitated. This significantly reduces asphalt / residue sample preparation time from whole crude.
[0046]
Depending on the nature of the AEBP and the crude, this process produces about 20 g of asphalt or residue from 5 ml of total crude. Preferred sample forms are sheets, thin films and droplets. These sample forms provide a sufficiently large surface area to rapidly cool or heat the sample. The higher the degree of decompression of the oven (the lower the pressure), the lower the oven temperature, so that the decomposition of the sample can be reduced. A preferred embodiment of the invention uses a fixed temperature oven with a sample equilibration time of 15 minutes or less, a constant vacuum buffer and a repeatability of 0.2%. The term “frozen” means cooling to a sufficiently low temperature so that water vaporization that causes sample damage does not occur for at least 30-60 seconds.
[Brief description of the drawings]
FIG. 1 shows fingerprint spectra (intensity vs. mass) of asphalts of groups I-IV.
FIG. 2 shows the fingerprint spectra (intensity vs. mass) of fractions derived from three representative crude oils (MEN, CL and BL).
FIG. 3 shows asphalt fingerprint spectra (intensity vs. mass) obtained from three representative crude oils (MEN, BCF-22 and CL).
FIG. 4 shows carbon number, molecular weight and strength vs. mass for rheology groups (RG) of groups I-V.

Claims (13)

A method for selecting crude oil or crude oil residue as a raw material for asphalt,
a) Select crude oil or crude oil residue,
Producing asphalt from the crude oil or crude oil residue,
Subjecting the asphalt sample to a rheology test to determine a rheology index for the sample;
Determining the average rheology index of the crude oil slate by repeating the rheology test and averaging the rheology index;
Assign a rheology group to the average rheology index;
For each of the rheology groups, calculate the average strength, aromaticity, carbon number and molecular weight,
Each molecular moment is expressed by the following formula:
Calculated by the sum of molecular moment = (strength × aromaticity) / (aromaticity),
Compare the molecular profiles of the rheology group of good asphalt and poor asphalt,
Determining the optimal asphalt composition from the molecular moment according to the procedure of using the molecular moment to confirm the statistical significance of the difference; and b) selecting crude oil or crude oil residue;
Subject the sample to high resolution mass spectrometry to determine multiple molecular groups;
Calculate the average value for each molecule group,
Determining the predicted rheological index of the sample;
Comparing the predicted rheological index to the rheological index of good and insufficient asphalt;
Determine the rheological group of the sample,
Predicting the suitability of crude oil slate for asphalt production based on the rheology group,
Including the step of predicting the asphalt performance of the crude oil or crude residue from the molecular composition according to a procedure for confirming the suitability of the crude oil slate for asphalt production as compared with the rheology group of good asphalt and poor asphalt. A method of selecting a characteristic crude oil or crude oil residue. The rheology index (RI) is given by the following formula:
RI = 13.8639-1.81864E-1 ^* Hc + 6.12843E-2Hi-4.153E-1 Hz-4.68191E-3Ni + 6.6655E-3Oi + 5.88057E-3Sm-1.42995E-1Sz-3.14998E-3 [ C5ARings-]-3.35754E-3 [C5ARings +] (wherein R ² = 0.95)
The method for selecting crude oil or crude oil residue according to claim 1, wherein:   The method according to claim 1, wherein the average value is obtained by multiple linear regression analysis, principal component regression analysis, partial least squares regression analysis, or conditional main spectrum analysis.   The method according to claim 1, wherein the crude oil is blended. The crude oil residue is
Cooling the crude oil sample to an average temperature of −200 to 0 ° C .;
Placing the cooled sample in a chamber so that the shape of the sample becomes small or thin enough to reach equilibrium within 15 minutes with the temperature in the chamber, ^{A process} having an absolute pressure of ⁻³ to 10 ⁻⁶ Torr and a fixed temperature of 340 to 540 ° C., so that the combination of the absolute pressure and the fixed temperature is equivalent to the boiling point in terms of atmospheric pressure of the generated residue And holding the sample in the chamber at the absolute pressure and the fixed temperature for 5 to 60 minutes until essentially only residue remains in the sample. The method for selecting crude oil according to claim 1, wherein: The asphalt is
Cooling the crude oil sample to an average temperature of −200 to 0 ° C .;
Placing the cooled sample in a chamber so that the shape of the sample becomes small or thin enough to reach equilibrium within 15 minutes with the temperature in the chamber, Having an absolute pressure of ⁻³ to 10 ⁻⁶ Torr and a fixed temperature of 340 to 540 ° C. As a result, the combination of the absolute pressure and the fixed temperature is equivalent to the boiling point in terms of atmospheric pressure of the generated residue. Holding the sample in the chamber at the absolute pressure and the fixed temperature for 5-60 minutes until essentially only residue remains in the sample; The method for selecting crude oil according to claim 1, wherein the crude oil is first produced as a residue sample.   The crude oil selection method according to claim 1, wherein at least one selected from the group consisting of an isochronous curve, a master curve, and a black diagram for expressing viscoelastic behavior is measured by the rheological test. .   The rheology test measures at least one item selected from the group consisting of a viscosity at 135 ° C, a SUPERPAVE PG temperature range (Tmax-Tmin), and a penetration at 25 ° C. Crude oil selection method. A method for predicting the potential quality in asphalt obtained from crude oil or a blend of crude oil of various origins,
Using detailed molecular composition and structural data obtained by high resolution mass spectrometry, the following formula:
C _n H _{(2n ± z)} −R
(In the formula, n is an integer of 0 or more , z is an integer of −4 to +44, and R is a heteroatom or a combination of heteroatoms)
Calculating a molecular moment consisting of strength, aromaticity, alkyl side chain length and molecular weight using a molecular library consisting of at least 100 molecular species represented by:
Associating a molecular moment with a global performance parameter that includes measurements of rheology related performance; and associating the global performance parameter with an actual pavement performance of asphalt made from crude oil or a crude oil blend. A method of predicting potential quality that is characteristic. The sample is
Sampling asphalt;
Separating a fraction of an asphalt sample; and producing a crude residue by distillation or total crude extraction technology, each of which includes a crude oil or a crude oil blend whose ingredients and proportions are known or unknown. The potential quality prediction method according to claim 9 , wherein the potential quality prediction method is generated by a method that can be performed as a target. The comprehensive performance parameter is a mathematical measure of at least one scale selected from the group consisting of conventional asphalt properties, viscosity at 135 ° C, SUPERPAVE PG temperature range (Tmax-Tmin), and penetration at 25 ° C. 10. The method for predicting potential quality according to claim 9 , wherein the potential quality can be calculated by combining them. The validity of the comprehensive performance parameter is
Calculating an average value of the global performance parameters from the individual values of the global performance parameters of all samples belonging to one crude oil slate;
Ranking the crude oil slate relative to other crude oil slate according to the average value of the global performance parameter; and the crude oil rank based on the average performance to determine the field performance of the asphalt pavement incorporating the crude oil or crude oil blend. 10. The method for predicting potential quality according to claim 9 , wherein the potential quality is tested by a method including a step of comparing with the method. Crude slate with respect molecular structure represented by the formula _{C n H (2n ± z)} -R,
Hydrocarbon molecular group of 10 ≦ z ≦ 26,
A sulfur molecular group of 12 ≦ z ≦ 22,
A monoatomic oxygen molecular group of 12 ≦ z ≦ 20 and a highly aromatic oxygen molecular group of 22 ≦ z ≦ 32 ,
High aromaticity _{S 2} molecule group of 14 ≦ x ≦ 20,
A diatomic oxygen molecule group of 4 ≦ z ≦ 22,
SO molecular group of 16 ≦ z ≦ 26,
NO molecular group of 9 ≦ z ≦ 21 ,
SO ₂ molecule group ,
Selected based on the mass intensity of the hydrocarbon molecular group of 28 ≦ z ≦ 44 and the highly aromatic sulfur molecular group of 24 ≦ z ≦ 34 ,
10. The method for predicting potential quality according to claim 9 , wherein no distinction is made for molecular groups where z> 32.

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